Deep Learning

1. Exact deep learning machines<br>Arni S.R. Srinivasa Rao<br>2. Multiscale representation learning for biomedical analysis<br>Abhishek Singh, Utkarsh Porwal, Anurag Bhardwaj, and Wei Jin<br>3. Adversarial attacks and robust defenses in deep learning<br>Chun Pong Lau, Jiang Liu, Wei-An Lin, Hossein Souri, Pirazh Khorramshahi, and Rama Chellappa<br>4. Deep metric learning for computer vision: A brief overview <br>Deen Dayal Mohan, Bhavin Jawade, Srirangaraj Setlur, and Venu Govindaraju<br>5. Source distribution weighted multisource domain adaptation without access to source data<br>Sk Miraj Ahmed, Dripta S. Raychaudhuri, Samet Oymak, and Amit K. Roy-Chowdhury<br>6. Deep learning methods for scientific and industrial research<br>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<br>7. On bias and fairness in deep learning-based facial analysis<br>Surbhi Mittal, Puspita Majumdar, Mayank Vatsa, and Richa Singh<br>8. Manipulating faces for identity theft via morphing and deepfake: Digital privacy<br>Akshay Agarwal and Nalini Ratha<br>