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Face Recognition and Analysis with Deep learning
Methods, Tools and Applications
- 1st Edition - June 1, 2029
- Authors: Dr. Ravindra S Hegadi, Dattatray D. Sawat
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 8 5 7 4 9 - 9
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 8 5 7 5 0 - 5
Face recognition and face analysis are being used by various law-enforcement, retail, and e-commerce solution developers for different purposes. Additionally, it is a no… Read more
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Request a sales quoteFace recognition and face analysis are being used by various law-enforcement, retail, and e-commerce solution developers for different purposes. Additionally, it is a non-invasive information gathering technique with multiple applications across industries
Face Recognition and Analysis with Deep Learning: Methods, Tools and Applications uses deep learning technology to detect faces in various environments, perform face recognition, and perform facial expression, age, gender, and geographical profile analysis. Giving in-depth information on every step of the process, it discusses solutions, performance analysis, and the various challenges in developing face recognition systems.
It provides:
•Different ways to prepare data and write data-pipelines.
•Optimization techniques for the deployment of models
•Use cases applications
This book is a complete reference guide for undergraduate and post graduate students, researchers, software developers and engineers in industry looking to make use of face recognition and analysis technology using deep learning methods.
- Presents state of art face recognition methods, tools and applications using deep learning.
- Explains the various challenges, solutions, and performance analyses when developing face recognition systems
- Presents tools such as Python, TensorFlow, OpenCV for use in developing algorithms, including code snippets
- Discusses current state-of-art approaches and future directions
Undergraduates, post graduates in computer vision, academic researchers, software developers and engineers in industry. (primary)
Table of contents – chapter headings 1. Introduction to face recognition2. Facial analysis3. Challenges in face recognition4. Introduction to deep learning5. Deep learning for face recognition6. Frameworks and tools7. Challenges and solutions8. Current state-of-art methods9. Model optimization techniques10. Applications and use cases
- No. of pages: 300
- Language: English
- Edition: 1
- Published: June 1, 2029
- Imprint: Academic Press
- Paperback ISBN: 9780323857499
- eBook ISBN: 9780323857505
DH
Dr. Ravindra S Hegadi
Ravindra S. Hegadi IEEE Senior Member, completed MCA in 1995, MPhil in 2003 and Ph. D. in 2007 from Gulbarga University, Kalaburagi. He worked as Lecturer in Government College, Raichur from February 1997 to January 2008, in Government First Grade College, Vijayanagar, Bangalore from January 2008 to July 2008, as Assistant Professor at Karnatak University, Dharwad from July 2008 to January 2012, as Associate Professor from February 2012 to January 2015 and as Professor from February 2015 to January 2020 in Solapur University, Solapur. He joined the Central University of Karnataka, Kadaganchi on 30th January 2020 as Associate Professor in Computer Science. He has published more than 150 research articles in reputed international journals and conference proceedings. He authored 2 books, edited 3 books, 30 book chapters, and one patent is published by him He has completed one UGC major research project worth Rs. 9.71 Lacs and currently he has two research projects from the Ministry of Electronics and IT, New Delhi each worth Rs. 50.06 Lacs.
Affiliations and expertise
Associate Professor in Computer Science, Central University of Karnataka, Kalaburagi, Karnataka, IndiaDS
Dattatray D. Sawat
Dattatray D. Sawat has completed B. Sc (Entire Computer Science) and M. Sc. (Computer Science) from Solapur University. He has qualified State Eligibility Test(SET) in January 2018. Currently, he is a research scholar and pursuing Ph.D. (Computer science) from Solapur University. His research area of interest includes Image Processing, Computer vision, Machine Learning/Deep Learning, Data Science and 3D Modelling. He received Visvesvaraya Ph. D. Scheme fellowship from the Ministry of Electronics and Information Technology (MeitY), Delhi
Affiliations and expertise
Research Scholar in Computer Science, Solapur University, Solapur, Maharashtra, India