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Generative Adversarial Networks and Deep Learning: Theory and Applications
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Generative Adversarial Networks and Deep Learning: Theory and Applications
This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. It concentrates on cutting-edge research in DL and GAN which includes creating new tools and methods for processing text, images, and audio.
256 pages, 12 Tables, black and white; 62 Line drawings, black and white; 44 Halftones, black and wh
| Mediji | Grāmatas Hardcover Book (Grāmata ar cieto muguriņu un vāku) |
| Izlaists | 2023. gada 10. aprīlis |
| ISBN13 | 9781032068107 |
| Izdevēji | Taylor & Francis Ltd |
| Lapas | 208 |
| Izmēri | 262 × 184 × 18 mm · 568 g |
| Valoda | Angļu |
| Redaktors | D Pathak, Pranav (MIT Art Design and Technology University, Pune, India) |
| Redaktors | Patil, Sonali (PCCoE, SPPU, Pune) |
| Redaktors | R Sakhare, Sachin (VIIT, Pune) |
| Redaktors | Raut, Roshani (Pimpri Chinchwad College of Engineering, Pune, India) |
