Technical Seminar Report
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Seminar report preparation. Sample reports and guidelines
The time is up! Submit your seminar report. Let us see some quick tips for preparing an excellent seminar report. Here I am listing some valuable resources for your seminar report preparation. Some are PDF documents, and the others are URLs. This is an excellent guideline, and the seminar template explains everything you need in a seminar report.
- Seminar Sample Report 1 (PDF Download)
- Seminar Sample Report 2 (PDF Download)
- Seminar Sample Report 3 (PDF Download)
- Seminar Sample Report 4 (PDF Download)
This PDF content includes Abstracts, acknowledgements, appendices, and references.
If you have not selected your seminar topic yet, and in research for the latest seminar topic, look at Collegelib seminar topic collection, and you could find a lot of technology topic ideas suitable for your branch of study and shortlist a few from them!
Remembering additional points and guidelines would help you prepare a better report. Found these Guidelines for writing the final report of my own final year seminar report.
Focus on how neatly you can write the following:
- Background of the study
- Research problem
- Objectives of the study
- Scope of the study
- Methodology of the study
- Structure of the reports
Additional mantras for preparation
- Do thorough research on your topic and take detailed notes.
- Create an outline of the seminar report, including an introduction, main points, conclusion, and recommendations.
- Include data and statistics to back up your arguments and claims.
- Use professional and clear language, avoiding jargon or technical terms that are not commonly understood by your audience.
- Include visual aids such as graphs, charts, and images to help illustrate your points.
- Use examples and case studies to highlight your main points and make them more relatable to your audience.
- Provide actionable recommendations that the audience can implement based on the information you have presented .
- Use a consistent formatting style throughout the report, including font size, font type, and spacing.
- Include a bibliography or reference list to cite the sources you used to gather information for the report.
- Edit and proofread your report carefully to ensure it is error-free and presents your ideas clearly and effectively.
- Consider using multimedia elements such as videos or audio recordings to enhance your presentation and engage your audience.
I like the way of references and the year of publication is presented in the report Seminar report references section.
- TFHE report, a seminar report sample
- An article from Columbia University , how to prepare a seminar or thesis in the best way?
- From Purdue University , is another great article to consider before writing a dissertation for your academic degree.
- Seminar report preparation, sample reports and guidelines (Collegelib.com)
We have covered helpful guidelines and sample report formats for your b-tech degree seminar. This Engineering Seminar guideline document is one of the most popular reference documents among all college students since its original Collegelib publication in 2010!
If you found this useful, please also check other similar articles at Collegelib.com
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Technical ieee seminar topics for cse with ppt and pdf report (2019).
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vtu ug project-report format
- VTU UG Project-Report Format
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- 1. A VTU UG Program BE Project Report Format Prepared by Prof.B.B.S.Kumar Research Scholar, Assistant Professor, Dept. of Electronics and Communication Engineering, RajaRajeswari College of Engineering, #14, Ramohalli Cross, Mysore Road, Kumbalagodu, Bengaluru-560074, Karnataka State, India. Email : [email protected] 2014
2. VISVESVARAYA TECHNOLOGICAL UNIVERSITY Jnana Sangama, Belgaum 590014 A PROJECT REPORT ON ADVANCED COMMUNICATION FOR QUADRIPLEGIA SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE AWARD OF DEGREE OF BACHELOR OF ENGINEERING IN ELECTRONICS AND COMMUNICATION ENGINEERING Submitted by B.MANJUNATHA MANISH KISHORE JAGGI USN: 1RR08EC004 USN: 1RR08EC012 VISHNU.C.S VISHNU R.PILLAI USN: 1RR08EC034 USN: 1RR08EC035 Under the guidance of Mr. B.B.S.KUMAR Assistant Professor DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING RAJARAJESWARI COLLEGE OF ENGINEERING BENGALURU-560074 2011-2012 3. RAJARAJESWARI COLLEGE OF ENGINEERING [ISO Certified 9000:2008, Affiliated to VTU, Belgaum, Approved by AICTE, New Delhi] #14, Ramohalli Cross, Mysore Road, Kumbalagodu, Bengaluru-74 DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING CERTIFICATE Certified that the project work entitled ADVANCED COMMUNICATION FOR QUADRIPLEGIA is a bonafide work carried out by B. Manjunatha , with USN: 1RR08EC004, Manish Kishore Jaggi, with USN: 1RR08EC012, Vishnu.C.S, with USN: 1RR08EC034 and Vishnu.R.Pillai, with USN: 1RR08EC035, in partial fulfillment for the award of Bachelor of Engineering in Electronics and Communication Engineering of the Visvesvaraya Technological University, Belgaum, during the year 2011 - 12. It is certified that all corrections/suggestions indicated for internal assessment have been incorporated in the report deposited in the departmental library. The project report has been approved as it satisfies the academic requirements in respect of project work prescribed for the said degree. External Viva Name of the Examiners: Signature with Date: 1. 2. Signature of the Guide Mr. B B S Kumar Signature of the HOD Prof. L N Das Signature of the Principal Dr. M S Bhagyashekar 4. DECLARATION We, B.MANJUNATHA (1RR08EC004), MANISH KISHORE JAGGI (1RR08EC012), VISHNU.C.S (1RR08EC034), VISHNU.R.PILLAI (1RR08EC035) students of 8th semester BE in Electronics and Communication Engineering, RajaRajeswari College of Engineering, Bangalore, hereby declare that the project work entitled ADVANCED COMMUNICATION FOR QUADRIPLEGIA submitted to the Visvesvaraya Technological University during the academic year 2011-12, is a record of an original work done by us under the guidance of Mr. B.B.S.KUMAR, Assistant Professor, Department of Electronics & Communication Engineering, RajaRajeswari College of Engineering, Bengaluru. This project work is submitted in partial fulfillment of the requirements for the award of the degree of Bachelor of Engineering in Electronics & Communication Engineering. The results embodied in this thesis have not been submitted to any other University or Institute for the award of any degree. Date: Place: Bengaluru B.Manjunatha Manish Kishore Jaggi Vishnu.C.S Vishnu.R.Pillai 5. I would like to dedicate this Project To my Beloved Parents 6. ACKNOWLEDGMENT Thanksgiving to those who directly and indirectly helped to complete the project work Ex: Chairman Principal HOD Guide Co-guide Project Co-ordinator Teaching Staff and Non Teaching Staff Industries/R&D Centres/Organisation Friends Family members B.Manjunatha Manish Kishore Jaggi Vishnu.C.S Vishnu.R.Pillai 7. ABSTRACT Past & Present trends techniques related to project work few lines Project title Scope of project Implemented on Simulation/Embedded/Hardware ex: MATLAB/C++/VB Methodology Testings, Experimental results analysis brief Throughput Achievements Merits 8. Contents Page no.s Front Page Certificate Declaration Dedication Acknowledgement Abstract Contents List of Figures List of Tables List of Flowcharts List of Acronyms Chapters Titles Page no.s Chapter 1: INTRODUCTION Chapter 2: LITERATURE SURVEY Chapter 3: IMAGE PROCESSING Chapter 4: EMBEDDED SYSTEM Chapter 5: HARDWARE/SOFTWARE DESCRIPTION Chapter 6: PROJECT IMPLEMENTATION Chapter 7: ALGORITHMS FOR PROJECT DESIGN Chapter 8: EXPERIMENTAL RESULTS AND DISCUSSION Chapter 9: CONCLUSION APPENDIX A APPENDIX B REFERENCES PUBLICATION DURING TENURE IN UG PROGRAM 9. LIST OF FIGURES Page no.s Fig.1.1 : DWT Fig.1.2 : DCT 10. LIST OF TABLES Page no.s Table 1.1 : DWT Table 1.2 : DCT 11. LIST OF FLOWCHARTS Page no.s Flowchart 1.1 : DWT Flowchart 1.2 : DCT 12. LIST OF EQUATIONS Page no.s Equ. 1.1 : DWT Equ. 1.2 : DCT 13. LIST OF ACRONYMS DWT : Discrete Wavelet Transform DCT : Discrete Cosine Transform 14. Advanced Communication for Quadriplegia Dept. of ECE, RRCE, Bengaluru 2013-14 Page 1 Chapter 1(font size 16) INTORDUCTION(font size 18) Give few lines introduction with respective to project related present trends techniques. (Font size 12) (Line spacing 1.5) (Paragraph gap 12 point) (Single tap at every paragraph begins) Objective of Project, Scope Brief explanation of project. 1.1 Any Industrial/R&D Centre/Organization Visit (Section font size 16) Mention few lines. Fig.1.1: Prof.B.B.S.Kumar Table 1.1: Publications Sl.No. Publications Journals 10 Conference 22 1.2 Area of field and domain explanation (in brief ) 1.2.1 Image Processing (Sub Section-font size 14) 1.3 Structure of Report Chapter 1: Chapter 2: Chapter 3: ............. ............. 15. Advanced Communication for Quadriplegia Dept. of ECE, RRCE, Bengaluru 2013-14 Page 2 Chapter 2 LITERATURE SURVEY Give introduction regarding literature survey- Why we need of ?......... few lines 2.1 Base Papers The order of paper references oAuthors Name oTitle of paper oPublication(ex : ieee, eslevier....)/Organisation/R&D Centres oISSN or ISBN oVol No. oIssue No. opp. No.(ex:1-23, 234-240) oYear of Publication Write on total 05 paper publication of journals in descending order of year, ex:2014, 2013, 2012, 2011.......................with base paper coming first, mention specifically Give brief explanation about paper description. 2.2 Motivation Regarding- how you motivated to do the project. 2.3 Need(Scope) of project 2.4 Previous Existing System With Demerits brief explanation. Results & Discussion in brief Methods Utility Tools used for implementation 2.5 Proposed System Explain in brief regarding proposed system comparing with previous work. 2.5.1 Define problem description/definition/statement 2.5.2 Methodology 2.5.3 Project limitation 2.5.4 Merits & Applications of proposed system 2.5.5 Tools used-explain in brief Note: This chapter can be added in the first chapter or can make separate chapter. 16. Advanced Communication for Quadriplegia Dept. of ECE, RRCE, Bengaluru 2013-14 Page 3 Chapter 3 Area of Domain Ex: IMAGE PROCESSING Explanation with Diagrams Relevant equations Merits Application 17. Advanced Communication for Quadriplegia Dept. of ECE, RRCE, Bengaluru 2013-14 Page 4 Chapter 4 Area of Domain Ex: EMBEDDED /SIMULATION/SOFTWARE/MANAGEMENT SYSTEM (related to project implementation) MATHEMATICAL PROOFS (if any) Explanation with Diagrams & Specifications Relevant equations Merits Application 18. Advanced Communication for Quadriplegia Dept. of ECE, RRCE, Bengaluru 2013-14 Page 5 Chapter 5 HARDWARE/SOFTWARE DESCRIPTION With respective to area of research work/ project Diagrams/Specification/Configuration Relevant equations Coding Techniques/Utility tools used Merits Application Related to project implementation 19. Advanced Communication for Quadriplegia Dept. of ECE, RRCE, Bengaluru 2013-14 Page 6 Chapter 6 PROJECT IMPLEMENTATION Explanation of working principle of project design Block Diagrams Relevant equations/Mathematical Merits Application related to project 20. Advanced Communication for Quadriplegia Dept. of ECE, RRCE, Bengaluru 2013-14 Page 7 Chapter 7 ALGORITHMS FOR PROJECT DESIGN 7.1 Algorithms of Image Processing Flowchart : Image Processing 7.2 Algorithms (If any) Flowchart : (If any) 7.3 Execution of project path link (software/hardware) 21. Advanced Communication for Quadriplegia Dept. of ECE, RRCE, Bengaluru 2013-14 Page 8 Chapter 8 EXPERIMENTAL RESULTS & DISCUSSION Input Specification (if any diagrams and tables) Output Specification (if any diagrams and tables) If hardware/embedded, add snapshots/photo of project model Mathematical Analysis Brief explanation of input/output Results discussion Throughput Achievements Comparisonsif any(bar charts and graphical characteristics representation) 22. Advanced Communication for Quadriplegia Dept. of ECE, RRCE, Bengaluru 2013-14 Page 9 Chapter 9 CONCLUSION Concluding with Scope and Results analysis Throughput Methodology Comparing with previous analysis Project work achievements 9.1 Future Enhancement Related to project work further what can be modified with present trends 23. Advanced Communication for Quadriplegia Dept. of ECE, RRCE, Bengaluru 2013-14 Page 10 APPENDIX A If any specification related to project work, not mentioned in main report ICs pin configuration......if any Equations.....if any Block diagrams.....if any 24. Advanced Communication for Quadriplegia Dept. of ECE, RRCE, Bengaluru 2013-14 Page 11 APPENDIX B If any specification related to project work, not mentioned in main report Software Description----if any Hardware Description---if any 25. Advanced Communication for Quadriplegia Dept. of ECE, RRCE, Bengaluru 2013-14 Page 12 REFERENCES More than 20+ should be given as references. In a descending order, publication year wise Ex: 2014, 2013, 2012, 2011, 2010, 2009...................etc., Order of references : paper publication, text books, websites Format : IEEE References citation should be mention in the main report text, whichever publication papers/text books/ websites is discussing/explaining related to topics. ex:, , .. 26. Advanced Communication for Quadriplegia Dept. of ECE, RRCE, Bengaluru 2013-14 Page 13 PUBLICATION DURING TENURE IN UG PROGRAM Example 1. B.B.S. Kumar & Dr. P. S. Satyanarayana, Compression and Denoising - Comparative Analysis from still Images using Wavelet Techniques, International Conference on Recent Trends in Engineering & Technology (ICRTET-2013), ITSI, Bangalore, India 24th March 2013, ISBN : 978-93-81693-88-18. Compression and Denoising - Comparative Analysis from still Images using Wavelet Techniques B. B. S. Kumar1 and Dr.P. S. Satyanarayana2 1 Dept. of ECE, Rajarajeswari College of Engineering, Bangalore. 2 E-mail : [email protected] Dept. Of ECE, Cambridge Institute of Technology, Bangalore. 1 , [email protected] Abstract With the growth of the multimedia technology over the past decades, the demand for digital information has increased dramatically. This enormous demand poses difficulties for the current technology to handle. One approach to overcome this problem is to compress the information by removing the redundancies present in it. This is the lossy compression scheme that is often used to compress information such as digital images. The main objective is to investigate the still image format compression and de-noising using different wavelet techniques. 2 The Compression and Denoising Comparative Analysis from still Images using Wavelet Techniques is implemented in software using MATLAB2012a version Wavelet Toolbox and 2-D DWT technique. The purpose is to analyze still images using different wavelets families such as Haar, Daubechies, Coiflets, Symlets, Discrete Meyer, Biorthogonal and Reverse Biorthogonal. The experiments and simulation is carried out on still image .jpg formats. This work tries to introduce wavelets and then some of its applications and technique in image processing. The scope of the work involves Compression and de-noising, image clarity and comparing the results of wavelet families, to find the effect of the decomposition and threshold levels and to find out energy retained (image recovery) and lost, knowing the best wavelet and so on. The wavelet differs from each other in image clarity and energy retaining. Each method is compared and classified in terms of its efficiency at different decomposition and threshold levels. Therefore, the image recovery is good and clarity, but the percentage of compression and retaining the energy is different. In order to quantify the performance of the de-noising, a noise is added to the still image and given as input to the de- 27. Advanced Communication for Quadriplegia Dept. of ECE, RRCE, Bengaluru 2013-14 Page 14 noising algorithm, which produces an image close to the original image. Keywords: Joint Production Experts Group (.jpg), Two Dimensional Discrete Wavelet Transform(2-D DWT) Attachment of National/International Conference(if any technical presentations) certificate photocopy Attachment of any awards received certificate photocopy
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105+ Technical IEEE Seminar Topics for CSE with PPT (2023)
Technical IEEE Seminar Topics for CSE with PPT and PDF Report (2023)
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THIS IS VTU FINAL YEAR PROJECT REPORT full report this report follows all the guidelines specified by vtu according to our college.
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- 1. VISVESVARAYA TECHNOLOGICAL UNIVERSITY BELAGAVI-590018 A Project Report On “FACESMASH: AI ASSISTED SOLUTION FOR MUSIC, CROWD MANAGEMENT AND SECURITY” Submitted in the partial fulfilment of the requirements for the award of the Degree of Bachelor of Engineering in Computer Science and Engineering Submitted by Drithiman M (1OX14CS022) Karuna Kiran Bhadra (1OX14CS022) Salman Ulla (1OX14CS022) Ransom David (1OX14CS022) Under the support and guidance of Ms. Jessy Janet Kumari Assistant Professor, Department of CSE Department of Computer Science and Engineering The Oxford College of Engineering Hosur Road, Bommanahalli, Bangalore-560068 (Approved by AICTE, New Delhi, Accredited by NBA, NAAC, New Delhi & Affiliated to VTU, Belagavi) 2017-2018
- 2. DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING THE OXFORD COLLEGE OF ENGINEERING Hosur Road, Bommanahalli, Bangalore-560068 (Approved by AICTE, New Delhi, Accredited by NBA, NAAC, New Delhi & Affiliated to VTU, Belagavi) CERTIFICATE Certified that the seminar entitled “FACESMASH” carried out by DRITHIMAN M (10X14CS022), KARUNA KIRAN BHADRA (1OX14CS039), SALMAN ULLA (1OX14CS50), RANSOM DAVID (1OX14CS0400) bonafide student of The Oxford College of Engineering, Bangalore in partial fulfilment for the award of the Degree of Bachelor of Engineering in Computer Science and Engineering of Visvesvaraya Technological University, Belagavi during the year 2017-2018. The project report has been approved as it satisfies the academic requirements in respect of project work prescribed for the said degree. Ms. Jessy Jane Kumari Dr. R.J. Anandhi Dr. R.V Praveena Gowda Project Guide H.O.D, Dept. of CSE Principal, TOCE External Viva Name of Examiner Signature with date
- 3. DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING THE OXFORD COLLEGE OF ENGINEERING Hosur Road, Bommanahalli, Bangalore-560068 (Approved by AICTE, New Delhi, Accredited by NBA, NAAC, New Delhi & Affiliated to VTU, Belagavi) Department Vision To establish the department as a renowned center of excellence in the area of scientific education, research with industrial guidance, and exploration of the latest advances in the rapidly changing field of computer science. Department Mission To producetechnocrats with creative technical knowledge and intellectual skills to sustain and excel in highly demanding world with confidence.
- 4. DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING THE OXFORD COLLEGE OF ENGINEERING Hosur Road, Bommanahalli, Bangalore-560068 (Approved by AICTE, New Delhi, Accredited by NBA, NAAC, New Delhi & Affiliated to VTU, Belagavi) DECLARATION We, student of Eighth semester B.E, at the Department of Computer Science and Engineering, The Oxford College of Engineering, Bangalore declare that the Seminar entitled “Turning Design Mock-Ups Into Code With Deep Learning” has been presented by me and submitted in partial fulfilment of course requirements for the award of degree in Bachelor of Engineering in Computer Science and Engineering discipline of Visvesvaraya Technological University, Belagavi during the academic year 2017-2018. Place: Bangalore Date:
- 5. ACKNOWLEDGEMENT The satisfaction and euphoria that accompany the successful completion of any task would be incomplete without the mention of the people who made it possible, whose constant guidance and encouragement crowned our efforts with success. I have great pleasure in expressing my deep sense of gratitude to my respected founder chairman late Shri S. Narasa Raju and to the respected chairman Shri S.N.V.L Narasimha Raju for having provided me with great infrastructure and well-furnished labs. I take this opportunity to express my profound gratitude to our respected Principal Dr. R V Praveena Gowda for his constant support and encouragement. I am grateful to the Vice Principal and Head of the Department Dr. R. J. Anandhi, Department of CSE, for her unfailing encouragement and suggestion given to me in the course of my Seminar work. Guidance and deadlines play a very important role in successful completion of the seminar report on time. I also convey my gratitude to Ms. Jessy Janet Kumari, Assistant Professor, Department of CSE, for having constantly monitored the development of the seminar report and setting up precise deadlines. Finally, a note of thanks to the Department of Computer Science Engineering, both teaching and non-teaching staff for their co-operation extended to me. i ABSTRACT Music plays an important role in an individual’s life. It is an important source of
- 6. entertainment and is often associated with a therapeutic role. Listening to music can help reduce stress according to many studies. It can help relieve a person from anxiety, depression, and other emotional and mental problems. Using traditional music players, a user has to manually browse through his playlist and select songs that would soothe his mood and emotional experience. This task was labor intensive and time consuming.The second functionality that we are implementing through the application is a Group-Emotion analyzer that can complement the music player in order to figure out the general emotional state of a gathering such as a party, or a club and dynamically adjust the music the pattern accordingly. This would, in essence, create a virtual DJ, and eliminate the need for a real one. Thus saving on cost and making the process more efficient. Next, we are going to provide throgh the application a data-driven crowd analysis system. This will take advantage of the multi-face tracking feature of the algorithm in use. From a regularly timed high-definition camera we will input images of the required area. The algorithm then tracks each decipherable face and provides approximate attribute values for the people whos faces are tracked. This means we get a random sample of the crowd to analyze. This can provide us with metrics such as the age groups to which the people in the crowd belong, the gender distribution, the emotional state of the crowd etc. This can immensely help people in professions such as event management, or to identify crisis spots in the crowd to form a kind of early warning system. Finally, we aim to provide a personal security platform throgh the application. The application can be used by security personnel in an restricted entry scenario to check against matches in the local database for people with known criminal background. This will act as a strong deterrent for people with bad intentions. The application will use Baysian networks in the server to act as a match modeller. Acceptable confidence level will be 70%. Our other aim is to innovate a roadmap to a new kind of UX for all software applications. One that works with human intuition and is smart. This will lower the barrier to use technology for all people and pave way for a new form of interaction. ii Table of Contents Acknowledgement i
- 7. Abstract ii Table of Contents iii List of Figures iv Chapter Page no 1. Preamble 1.1 Definition 1.2 Overview 1.3 About 1.4 Problem Definition 1.5 Problem Explanation 2. SYSTEM DESIGN 3 SYSTEM REQUIRMENTSPECIFICATION 4 SYSTEM DESIGN AND MODELLING 5 IMPLEMENTATION 6 SOFTWARE TESTING 7 INFERENCEFROM RESULTS 8 CONCLUSION 12 REFERENCES 13 iii List of Figures Figure Page No.
- 8. Fig 2.1 Airbnb’s demo of their internal AI tool to go from drawings to code 4 Fig 2.2 The SketchCodemodel takes drawn wireframes and generates HTML code 5 Fig 2.3 Image captioning models generate descriptions of sourceimages 5 Fig 2.4 The pix2code dataset of generated website images and sourcecode 6 Fig 2.5 Turning colourful website images into hand-drawn versions 7 Fig 2.6 Training the model using sequences of tokens as input 8 Fig 2.7 Visualizing the BLEU score 9 Fig 2.8 One drawing gives rise to many styles generated simultaneously 10 iv CHAPTER 1 INTRODUCTION 1.1 INTRODUCTION TO FACIAL RECONGNITION AND MOOD DETECTION
- 9. FaceSmash 2018 Department of CSE, TOCE 2 A facial recognition system is a technology capable of identifying or verifying a person from a digital image or a video frame from a video source. There are multiples methods in which facial recognition systems work, but in general, they work by comparing selected facial features from given image with faces within a database. While initially a form of computer application, it has seen wider uses in recent times on mobile platforms and in other forms of technology, such as robotics. It is typically used in security systems and can be compared to other biometrics such as fingerprint or eye iris recognition systems. Recently. it has also become popular as a commercial identification and marketing tool. In the case of Mood Detection, Emotion recognition is the process of identifying human emotion, most typically from facial expressions. This is both something that humans do automatically but computational methodologies have also been developed. The above process leverages techniques from multiple areas, such as signal processing, machine learning, and computer vision. The computers use different methods to interpret emotion such as Bayesian networks.  Fig 1.1 Shows All the emotions that can be classified. 1.2 OBJECTIVES AND GOALS Facial expressions are important in facilitating human communication and interactions. Also, they are used as an important tool in behavioural studies and in medical rehabilitation. Facial image based mood detection techniques may provide a fast and practical approach for non-invasive mood detection. The purpose of the present study was to develop an intelligent system for facial image based expression classification using committee neural networks.
- 10. FaceSmash 2018 Department of CSE, TOCE 3 Facial expressions and related changes in facial patterns give us information about the emotional state of the person and help to regulate conversations with the person. Moreover, these expressions help in understanding the overall mood of the person in a better way. Facial expressions play an important role in human interactions and non-verbal communication. Classification of facial expressions could be used as an effective tool in behavioural studies and in medical rehabilitation. Facial expression analysis deals with visually recognizing and analysing different facial motions and facial feature changes. The main objective of the system being built is to be able to recognize facial expression and predict the emotion based upon a present neural structure for recognition for the same. The system should be able to correctly identify the correct facial expression when presented an image from subjects used in training or in initial testing. Committee neural networks offer a potential tool for image based mood detection and even crowd analysis and management. It can also be use on one or more than one face per transaction and can be helpful in crowd based analysis of mood and intent of the crowd. 1.3 Existing System Research efforts in human–computer interaction are focused on the means to empower computers (robots and other machines) to understand human intention, e.g. speech recognition and gesture recognition systems . In spite of considerable achievements in this area during the past several decades, there are still a lot of problems, and many researcher are still trying to resolve them. Besides, here is another important but ignored mode of Communication that may be important for more natural interaction emotion plays an important role in contextual understanding of messages from others in speech or visual forms. There are numerous areas in human–computer interaction that could effectively use the capability to understand emotion. For example, it is accepted that emotional ability is an essential factor for the next-generation personal robot, such as the Sony AIBO. It can also play a significant role in intelligent room and affective computer tutor. Although limited in number compared with the efforts being made towards intention-translation means, some researchers are trying to realise man machine interfaces with an emotion understanding capability. Most of them are focused on facial expression recognition and speech signal analysis. Another possible approach for emotion recognition is physiological signal analysis. We believe that this is a more natural means of emotion recognition, in that the influence of emotion on facial expression or speech can be suppressed relatively easily, and emotional status is inherently reflected in the activity of the nervous system. In the field of psychophysiology, traditional tools for the investigation of human emotional status are based on the Recording and statistical analysis of physiological signals from both the central and autonomic nervous systems.
- 11. FaceSmash 2018 Department of CSE, TOCE 4 Researchers at IBM recently reported an emotion recognition device based on mouse- type hardware. Picard and colleagues at the MIT Media Laboratory have been exerting their efforts to implement an affective computer since the late 1990s. First, their algorithm development and performance tests were carried out with data that reflect intentionally expressed emotion. The existing system is too naïve to work with and can not have any further evolutionary growth to it. The existing system proposes to use the Viola-Jones algorithm to classify facial expressions and select playlist. Fig 1.1 will detail the architecture of the system. Fig 1.1 shows the arch followed by viola-jones Open CV method of facial feature recognition. The existing system uses OpenCV to classify the face emotions. This may lead to incompatibility in all devices, as on the systems that do not run OpenCV, the code will not perform as expected. 1.4 Proposed System Our proposed system follows the following the action pattern for the required use cases: USE CASE I : Personal Music Player 1. User triggers camera to take a selfie 2. Captured picture raw data is sent to server
- 12. FaceSmash 2018 Department of CSE, TOCE 5 3. Server uses a Bayesian network to evaluate the data and produce classification of the input. 4. This classification is used to select a playlist that best matches the emotional state of the user. 5. The audio files corresponding to the playlists are then streamed one by one to the application. 6. The applications provides a player front-end to control the playback. USE CASE II : Group-specific Music Player Same methodology as above is used. Except, the classification is put through a further analysis phase to find a average emotion value. USE CASE III : Crowd analytics 1. Capture crowd image for the requred area. 2. Captured raw data sent to server. 3. Server classifies the legitimate faces in the raw data. 4. Algorithm determines the attributes associated with each face. 5. For emotion, majority attributes are selected to represent the overall emotion. 6. For age, a percentage data representation provides the approximate percentage of the crowd for each age bracket. 7. For gender, a majority value is returned. 8. All data are displayed in the application. 9. User decides the policies relating to the output. USE CASE IV: Facial recognition platform, to be used as a security tool at checkpoints. 1. Picture of the entering person is captured through the application. 2. The picture is sent over to the server containing the database of local and regional criminal profiles. 3. The face is deconstructed into mesh. 4. Mesh is compared against database. 5. If match is found then a alert is raised discreetly. 6. Else, the person is allowed to enter. The Fig. below shows the proposed system flow diagram of the application FaceSmash.
- 13. FaceSmash 2018 Department of CSE, TOCE 6 Fig. 1.1 Use case diagram of proposed system 1.5 Summary FaceSmash is an android application that is aimed to realize the reality of facial detection and emotion detection using artificial intelligence and machine learning. This will be then use for the above said use cases, ai assisted solution for music playing, crowd management and security. The project contains two three modules, 1. Emotion based music suggestion 2. Crowd Analyzer. 3. Facial Recongition.
- 14. FaceSmash 2018 Department of CSE, TOCE 7 CHAPTER 2 SYSTEM DESIGN 2.1 Design Consideration Facial expressions play a significant role in human dialogue. As a result, there has been considerable work done on the recognition of emotional expressions and the application of this research will be beneficial in improving human-machine dialogue. One can imagine the improvements to computer interfaces, automated clinical (psychological) research or even interactions between humans and autonomous robots. Unfortunately, a lot of the literature does not focus on trying to achieve high recognition rates across multiple databases. In this project we develop our own mood detection system that addresses this challenge. The system involves pre-processing image data by normalizing and applying a simple mask, extracting certain (facial) features using PCA and Gabor filters and then using SVMs for classification and recognition of expressions. Eigenfaces for each class are used to determine class-specific masks which are then applied to the image data and used to train multiple, one against the rest, SVMs. We find that simply using normalized pixel intensities works well with such an approach. Fig 1.1 details the system overview. Fig 1.1 Overview of System Design. We performed pre-processing on the images used to train and test our algorithms as follows: 1. The location of the eyes is first selected manually 2. Images are scaled and cropped to a fixed size (170 x 130) keeping the eyes in all images aligned 3. The image is histogram equalized using the mean histogram of all the training images to make it invariant to lighting, skin colour etc. 4. A fixed oval mask is applied to the image to extract face region. This serves to eliminate the background, hair, ears and other extraneous features in the image which provide no information about facial expression.
- 15. FaceSmash 2018 Department of CSE, TOCE 8 This approach works reasonably well in capturing expression-relevant facial information across all databases. Examples of pre-processed images from the various datasets are shown in Fig 1.2 below. Fig 1.2 Top: Original images, Bottom: Processed images with mask Normalized pixel intensities: Every image in our training set is normalized by subtracting the mean of all training set images. The masked region is then converted to a column vector which forms the feature vector. This is a common (albeit naïve) approach and produces a feature vector of length 15,111 elements. Gabor filter representations: Gabor filters are often used in image processing and are based on physiological studies of the human visual cortex. The use of Gabor filtered facial images has been shown to result in improved accuracy for facial expression recognition. One approach to using these filters is to generate a bank of filters across multiple spatial frequencies and orientations. The filtered outputs are then concatenated, and down-sampling or PCA is often used to reduce dimensionality. We use an approach similar to that provides competitive results, and use the L1 norm of each of the Gabor bank features for a given image. Our Gabor bank contains filters at 5 spatially varying frequencies and 8 orientations. In the below Fig 1.3 , we show examples of Gabor features.
- 16. FaceSmash 2018 Department of CSE, TOCE 9 Fig 1.3 Top: Pre-processed images, Bottom: L1 images with Gabor bank features 2.2 System Architecture Two types of parameters were extracted from the facial image: real valued and binary. A total of 15 parameters consisting of eight real-valued parameters and seven binary parameters were extracted from each facial image. The real valued parameters were normalized. Generalized neural networks were trained with all fifteen parameters as inputs. There were seven output nodes corresponding to the seven facial expressions (neutral, angry, disgust, fear, happy, sad and surprised). Based on initial testing, the best performing neural networks were recruited to form a generalized committee for expression classification. Due to a number of ambiguous and no-classification cases during the initial testing, specialized neural networks were trained for angry, disgust, fear and sad expression. Then, the best performing neural networks were recruited into a specialized committee to perform specialized classification. A final integrated committee neural network classification system was built utilizing both generalized committee networks and specialized committee networks. Then, the integrated committee neural network classification system was evaluated with an independent expression dataset not used in training or in initial testing. A generalized block diagram of the entire system is shown in Figure 2.4.
- 17. FaceSmash 2018 Department of CSE, TOCE 10 Fig. 2.4 Overall block diagram of methodology Facial expression images are to be obtained from the Cohn-Kanade database. The database contains facial images taken from 97 subjects with age ranging from 18 to 30 years. The database had 65 percent female subjects. Fifteen percent of the subjects were African-American and three percent were Asian or Latino. The database images were taken with a generic camera. The camera was located directly in front of the subject. The subjects performed different facial displays (single action units and combinations of action units) starting and ending with a neutral face. The displays were based on descriptions of prototypic emotions (i.e., neutral, happy, surprise, anger, fear, disgust, and sad). The image sequences were digitized into 640 by 480 pixel arrays with 8-bit precision for grayscale values. Two types of parameters were extracted from the facial images of 97 subjects: (1) real valued parameters and (2) binary parameters. The real valued parameters have a definite value depending upon the distance measured. This definite value was measured in number of pixels. The binary measures gave either a present (= 1) or an absent (= 0) value. In all, eight real valued measures and seven binary measures were obtained.
- 18. FaceSmash 2018 Department of CSE, TOCE 11 A number of parameters, both real-valued and binary, were extracted and analysed to decide their effectiveness in identifying a certain facial expression. The features which did not provide any effective information of the facial expression portrayed in the image were eliminated and were not used in the final study. The real valued and binary feature selection was inspired by the FACS. Fig 2.5 Shows the methodology of image processing. Real valued parameters (shown in Fig. 2.6) 1. Eyebrow raise distance – The distance between the junction point of the upper and the lower eyelid and the lower central tip of the eyebrow. 2. Upper eyelid to eyebrow distance – The distance between the upper eyelid and eyebrow surface. 3. Inter-eyebrow distance – The distance between the lower central tips of both the eyebrows. 4. Upper eyelid – lower eyelid distance – The distance between the upper eyelid and lower eyelid. 5. Top lip thickness – The measure of the thickness of the top lip. 6. Lower lip thickness – The measure of the thickness of the lower lip. 7. Mouth width – The distance between the tips of the lip corner. 8. Mouth opening – The distance between the lower surface of top lip and upper surface of lower lip.
- 19. FaceSmash 2018 Department of CSE, TOCE 12 Fig 2.6 Real-valued measures from a sample neutral expression image. 1-eyebrow raise distance, 2-upper eyelid to eyebrow distance, 3-inter eyebrow distance, 4-upper eyelid to lower eyelid distance, 5-top lip thickness, 6-lower lip thickness, 7-mouth width, 8-mouth opening. Binary parameters 1. Upper teeth visible – Presence or absence of visibility of upper teeth. 2. Lower teeth visible – Presence or absence of visibility of lower teeth. 3. Forehead lines – Presence or absence of wrinkles in the upper part of the forehead. 4. Eyebrow lines – Presence or absence of wrinkles in the region above the eyebrows. 5. Nose lines – Presence or absence of wrinkles in the region between the eyebrows extending over the nose. 6. Chin lines – Presence or absence of wrinkles or lines on the chin region just below the lower lip. 7. Nasolabial lines – Presence or absence of thick lines on both sides of the nose extending down to the upper lip. These binary parameters are depicted in Fig 2.7
- 20. FaceSmash 2018 Department of CSE, TOCE 13 Fig 2.7 Binary measures from sample expression images. 1-upper teeth visible, 2-lower teeth visible, 3-forehead lines, 4-eyebrow lines, 5-nose lines, 6-chin lines, 7-nasolabial lines. 2.4 Use Case Diagrams 2.5 Sequence Diagram 2.6 Dataflow Diagram
- 21. FaceSmash 2018 Department of CSE, TOCE 14 Chapter 3 System Requirement Specification Requirement Specification is a complete specification of the behaviour of the system to be developed. It includes a set of use cases that describes all the interactions user will have with the software. Use cases are also known as functional requirements. In addition to use cases, the document also contains non-functional requirements, Non-functional requirements are requirements which impose constraints on design on implementation. 3.1 Software Requirements Android Operating System. Version 4.4 (KitKat) and above. Good network connectivity to the Internet. Stream-configurable server system. Google TensorFlow for training the classifier. 3.2 Hardware Requirements Smartphone running required Android operating system version. At least one camera with a minimum required sensor Megapixel count of 5MP. Server configuration: at least 8GB DRAM. Server configuration: NVIDIA GPU above GeForce 830M recommended. Server configuration: Intel Core 2 Duo and above recommended.
- 22. FaceSmash 2018 Department of CSE, TOCE 15 Chapter 4 Implementation 4.1 Selection of Platform Android Studio is an integrated development environment (IDE) for the Android platform. It simplifies app development. Though offered by Google, seasoned Java developers will immediately recognise that the toolkit is a version of IntelliJ IDEA. According to IDC, globally, Android’s share of the smartphone market is about 45 per cent. The best part is that Android is open source and learning it is not at all difficult. Students and professionals want to, at least, know its basics. There are many platforms, like Android Studio, where even beginners can get into Android development. Android Studio is a cross-platform integrated development environment (IDE) for developing on the Android platform. It is written in Java and is available for Linux, Windows as well as for macOS. Eclipse, which also provided Android development tools, has been replaced by Android Studio as Google’s primary IDE for native Android application development. The main reason for this move is because Eclipse was not stable. Android Studio offers a better Gradle build environment, smarter short cuts, an improved user interface (UI) designer, a better memory monitor, an improved string translation editor and better speed. The build system in Android Studio replaces the Ant system used with Eclipse ADT. It can run from the menu as well as from the command line. It allows you to track memory allocation as it monitors memory use. It has built-in support for the Google Cloud Platform, making it easy to integrate Google Cloud Messaging and App Engine. It also comes with inline debugging, and performance analysis tools. Android Studio has Android Virtual Device (AVD) which comes with emulators for Nexus 6 and Nexus 9 devices. It also offers build variants and the capability to generate multiple apk files. Whenever one compiles a program, the configured lint and IDE inspections run automatically. Configuration Installation Before you set up Android Studio in Linux, you need to install JDK 6 or higher. In fact, JDK 7 is required for developing Android 5.0 or above. The other requirements are a minimum of 2GB RAM (though 4GB is recommended), 400MB hard disk space and at least 1GB for the Android SDK, emulator system images, caches, GNU C Library (glibc) 2.15 or later, etc. After installing Android Studio and setting it up, go to the SDK manager to update the required tools, platforms, etc, required for app-building. These packages provide the basic SDK tools for app development, without an IDE. If you prefer to use a different IDE, the standalone Android SDK tools can be downloaded. One can set up an update channel to Stable by going to: File > Settings > Appearance & Behaviour System Settings > Updates as shown in the figure 4.1 below.
- 23. FaceSmash 2018 Department of CSE, TOCE 16 Fig. 4.1 Shows how updates have to be installed. Fig 4.2 Shows how Samples can be imported to android Studios.
- 24. FaceSmash 2018 Department of CSE, TOCE 17 4.2 Functional Descriptions of Modules
- 25. FaceSmash 2018 Department of CSE, TOCE 18 Chapter 5 System Testing
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in the report. The seminar report has been approved as it satisfies the academic requirement in respect of Technical Seminar work prescribed for the said Degree. Signature of the Guide ………. Professor Signature of Co-ordinator (s) ………………… Associate Professor Signature of the HOD …………………
Seminar Report Format vtu 8th sem Uploaded by Akhilesh Bhushan Copyright: Attribution Non-Commercial (BY-NC) Available Formats Download as DOCX, PDF, TXT or read online from Scribd Flag for inappropriate content 71% 29% of 3 1 K.L.E. Institute of Technology Opposite Airport, Gokul, Hubli - 580030. Department of Computer Science & Engineering
The Seminar Report format is as follows: 1. Front Sheet should be same as specified. 2. Certificate from College 3. Acknowledgement (One page) 4. Contents with page numbers5. Abstract (One/Two pages) Chapter 1:Introduction Chapter 2:Related work/Literature survey Chapter 3:Implementation (if applicable) Chapter 4:Applications
DEPARTMENT OF CIVIL ENGINEERING. CERTIFICATE. This is to certify that the Technical seminar work entitled "U-BOOT TECHNOLOGY IN. CONSTRUCTION" carried out by Mr. HEMANTH GOWDA S S, bearing USN. 1GA17CV405, a bonafide student of GLOBAL ACADEMY OF TECHONOLOGY in. partial fulfilment for the award of degree of Bachelor of Engineering in CIVIL.
(PDF) Technical seminar report Technical seminar report January 2019 Authors: Jayati Vijaywargiya Indian Institute of Space Science and Technology Discover the world's research...
This is an excellent guideline, and the seminar template explains everything you need in a seminar report. Seminar Sample Report 1 (PDF Download) Seminar Sample Report 2 (PDF Download) Seminar Sample Report 3 (PDF Download) Seminar Sample Report 4 (PDF Download) This PDF content includes Abstracts, acknowledgements, appendices, and references.
The dimension of the seminar report should be in A4 size. The project report should be hard bound using flexible cover of the thick art paper. Two copies of the report (hard copy only) should be submitted. 3 TYPING INSTRUCTIONS: One and a half spacing should be used for typing the general text. The general text
5. Contents of Report Every copy of the report must contain • Inner title page (White) • Outer title page with a plastic cover • Certificate in the format enclosed both from the college and the organization where the project is carried out. • An abstract (synopsis) not exceeding 100 words, indicating salient features of the work.
Vtu Seminar Report Format Pdf - bodyfasr FORMAT OF SEMINAR REPORT. 1. Paper Size: A- 4 size bond paper. 2. Margins: Top: 1" (1 inch=cm). Bottom: " (cm). Left: ". Right: " . 3. Posts about VTU Final seminar format written by KLEIT E&C Dept. Certificate Format - Final seminar - VTU 8th semester - Updated.
Project reports should be typed neatly only on one side of the paper with 1.5 or double line spacing on a A4 size bond paper (210 x 297 mm). The margins should be: Left - 1.25″, Right - 1″, Top and Bottom - 0.75″. The total number of reports to be prepared are One copy to the department One copy to the concerned guide (s)
As a part of the course Research Methodology & IPR, presenting the seminar is mandatory. The CIE marks awarded for Resaerch/Technical Seminar shall be based on the evaluation of Seminar Report, Presentation skills and performance in Question and Answer session in the ratio 50:25:25. Seminar is to be considered for 20 marks. Remaining 20 marks ...
The dimension of the seminar report should be in A4 size. 3. PREPARATION FORMAT: 3.1 Abstract - Abstract should be one page synopsis of the seminar report typed 1.5 line spacing, Font Style Times New Roman and Font Size 12. 3.2 Table of Contents - A specimen copy of the Table of Contents of the seminar report is given in Appendix
iot technical ai ml vtu seminar seminar-paper seminar-notes vtu-technical-seminar Updated Aug 14, 2021; davidstutz / seminar-cnn-image-retrieval Star 3. Code Issues ... Presentation and Report (Extended abstract) for a selected paper created during Computer vision seminar (MA-INF 2206).
There are no absolute rules about the details of report production, because every report must be totally adapted to the needs of its reader. This Guide suggests laws of good report writing, but only because in the field of communication, laws should be generally applied but broken if necessary. For example, the second law concerns brevity.
A VTU UG Program BE Project Report Format Prepared by Prof.B.B.S.Kumar Research Scholar, Assistant Professor, Dept. of Electronics and Communication Engineering, RajaRajeswari College of Engineering, #14, Ramohalli Cross, Mysore Road, Kumbalagodu, Bengaluru-560074, Karnataka State, India. Email : [email protected] 2014. VISVESVARAYA ...
Technical IEEE Seminar Topics for CSE with PPT and PDF Report: Technical field is all about facing competition and making something better. Technical field requires a lot of seminars and presentation to present your views and ideas.
VTU Seminar report front page LATEST. This report is in accordance to the guidelines specified by vtu according to our college athiathi3 Follow Advertisement Advertisement Recommended VTU Seminar report front pages LATEST athiathi3 2.5k views • 7 slides Summer Bridge I-2014 Poster Board Hoai nguyen 163 views • 1 slide Tony tonyhoney 2.4k views •
THIS IS VTU FINAL YEAR PROJECT REPORT full report this report follows all the guidelines specified by vtu according to our college. athiathi3 Follow Advertisement Recommended Ignou MCA mini project report Hitesh Jangid 12.8k views • 110 slides Mcsp 060 project guidelines july 2012 Abhishek Verma 5.7k views • 24 slides Complete-Mini-Project-Report
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