Deep Learning: Handbook of Statistics, cartea 48
Arni S.R. Srinivasa Rao, Venu Govindaraju, C. R. Raoen Limba Engleză Hardback – mar 2023
- Provides the authority and expertise of leading contributors from an international board of authors
- Presents the latest release in the Handbook of Statistics series
- Includes the latest information on Deep Learning
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Specificații
ISBN-13: 9780443184307
ISBN-10: 0443184305
Pagini: 270
Dimensiuni: 152 x 229 mm
Greutate: 0.53 kg
Editura: ELSEVIER SCIENCE
Seria Handbook of Statistics
ISBN-10: 0443184305
Pagini: 270
Dimensiuni: 152 x 229 mm
Greutate: 0.53 kg
Editura: ELSEVIER SCIENCE
Seria Handbook of Statistics
Public țintă
Statisticians, mathematicians and studentsCuprins
1. Exact deep learning machines
Arni 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
Arni 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