Generative Adversarial Networks Deep (53 results)

Paperback. Condition: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Paperback. Condition: Very Good-. 1st Edition (Unstated). 7.38 X 0.4 X 9.25 inches; 214 pages; Light rubbing (shelf wear) to covers. Very Good condition otherwise. No other noteworthy defects. No markings. ; - Your satisfaction is our priority. We offer free returns and respond promptly to all inquiries. Your item will be carefully cushioned in bubble wrap and securely boxed. All orders ship on the same or next business day. Buy with confidence.

Condition: New. pp. 245.

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Softcover. Condition: New. Dust Jacket Condition: no dj. First. Deep fake detection is a critical component of ensuring the authenticity and integrity of digital media, and generative adversarial networks (GANs) are playing an increasingly important role in this field. This book provides a comprehensive overview of the latest GAN-based techniques for deep fake detection, including image-based methods, video-based methods, and audio-based methods. The authors discuss the challenges and limitations of GANs in deep fake detection, including the need for more robust and efficient detection schemes, the importance of model interpretability, and the potential for GANs to be used for malicious purposes. They also present strategies for addressing these challenges, including the use of transfer learning, data augmentation, and adversarial training. Throughout the book, the authors draw on real-world examples and case studies to illustrate the practical applications of GANs in deep fake detection, including image recognition, video analysis, and audio processing. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condition: New. Dust Jacket Condition: no dj. First. The book 'Generative Adversarial Networks in Deep Fake Detection' explores the sophisticated techniques used to identify and counteract synthetic media created through GANs. It covers the underlying architecture of generative adversarial networks and their application in detecting manipulated images and videos. The discussion extends to the challenges of maintaining authenticity in digital content and the evolving landscape of deep fake technology. This resource offers insights into the technological arms race between creators of deep fakes and those developing detection methods, emphasizing the importance of robust AI systems for digital trust. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condition: New. Dust Jacket Condition: no dj. First. Generative adversarial networks (GANs) are a rapidly evolving field of machine learning, aimed at generating realistic and diverse data samples. This book provides a comprehensive guide to GANs, covering topics such as GAN architecture, training methods, and applications. By examining the complex relationships between GANs, deep learning, and data generation, the book offers insights into the development of effective GAN strategies. With its focus on real-world examples and case studies, Deep Dive into Generative Adversarial Networks is an essential resource for researchers, developers, and practitioners seeking to leverage GANs for a wide range of applications. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condition: New. Dust Jacket Condition: no dj. First. Deep Dive into Generative Adversarial Networks' Hidden Layers presents a comprehensive guide to the complex process of generative adversarial networks, ones that span the intricate landscape of neural networks, deep learning, and machine learning. By examining the neural mechanisms underlying GANs, this book identifies key areas for intervention, from training algorithms to evaluation metrics. With a focus on the dynamic interplay between GANs and the brain's cognitive processes, 'Deep Dive into Generative Adversarial Networks' Hidden Layers' offers a fascinating glimpse into the future of AI and the role of GANs in shaping the creative process. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condition: New. Dust Jacket Condition: no dj. First. Generative Adversarial Networks (GANs) have revolutionized the field of deep learning, enabling the creation of realistic and diverse synthetic data. This book provides a comprehensive overview of the underlying principles and architectures of GANs, as well as their applications in computer vision, natural language processing, and other areas. By exploring the strengths and limitations of GANs, readers can gain a deeper understanding of their potential and pitfalls, and develop the skills necessary to design and train their own GAN-based models. With its rigorous mathematical derivations and practical examples, this book is an essential resource for anyone interested in the cutting-edge field of GANs. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.