Deep Learning, Volume 48 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Generative Adversarial Networks for Biometric Synthesis, Data Science and Pattern Recognition, Facial Data Analysis, Deep Learning in Electronics, Pattern Recognition, Computer Vision and Image Processing, Mechanical Systems, Crop Technology and Weather, Manipulating Faces for Identity Theft via Morphing and Deepfake, Biomedical Engineering,� and more.
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Table of Contents
1. Exact deep learning machinesArni S.R. Srinivasa Rao
2. Multiscale representation learning for biomedical analysis
Abhishek Singh, Utkarsh Porwal, Anurag Bhardwaj, and Wei Jin
3. Adversarial attacks and robust defenses in deep learning
Chun Pong Lau, Jiang Liu, Wei-An Lin, Hossein Souri, Pirazh Khorramshahi, and Rama Chellappa
4. Deep metric learning for computer vision: A brief overview
Deen Dayal Mohan, Bhavin Jawade, Srirangaraj Setlur, and Venu Govindaraju
5. Source distribution weighted multisource domain adaptation without access to source data
Sk Miraj Ahmed, Dripta S. Raychaudhuri, Samet Oymak, and Amit K. Roy-Chowdhury
6. Deep learning methods for scientific and industrial research
G.K. Patra, Kantha Rao Bhimala, Ashapurna Marndi, Saikat Chowdhury, Jarjish Rahaman, Sutanu Nandi, Ram Rup Sarkar, K.C. Gouda, K.V. Ramesh, Rajesh P. Barnwal, Siddhartha Raj, and Anil Saini
7. On bias and fairness in deep learning-based facial analysis
Surbhi Mittal, Puspita Majumdar, Mayank Vatsa, and Richa Singh
8. Manipulating faces for identity theft via morphing and deepfake: Digital privacy
Akshay Agarwal and Nalini Ratha
