AI-Generated Image and Video Synthesis
Editat de Arvind Mewada, Mohd. Aquib Ansari, Nagendra Singh, Shahnawaz Ahmaden Limba Engleză Hardback – 11 aug 2026
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Specificații
ISBN-10: 1394403119
Pagini: 192
Greutate: 0.53 kg
Ediția:1. Auflage
Editura: John Wiley & Sons, Inc.
Cuprins
Contributors xi
Foreword xiii
About the Editors xv
Preface xvii
Acknowledgements xix
Acronyms xxi
Introduction xxiii
1 Introduction to AI-generated Image and Video Synthesis 1
Arvind Mewada, Mohd. Aquib Ansari, Shahnawaz Ahmad, and Nagendra Singh
1.1 Introduction 1
1.2 Foundations of AI-generated Media 2
1.3 Image Synthesis Techniques 5
1.4 Video Synthesis and Manipulation 9
1.5 Applications for AI-generated Media 12
1.6 Ethical and Societal Considerations 14
1.7 Future Directions and Challenges 17
1.8 Conclusion 19
2 LoomNet: An Assam Handloom Fabric Dataset 23
Anindita Das and Aniruddha Deka
2.1 Introduction 23
2.2 Methodology 25
2.3 Discussion and Future Work 30
2.4 Conclusion 31
3 Sensors-to-synthesis: Edge AI and IoT for Generative Visual Systems 35
Swati Vishnoi, Ankur Sisodia, Mayank Deep Khare, and Ajay Kumar Yadav
3.1 Introduction 35
3.2 Background and Literature Review 36
3.3 Architectural Framework 38
3.4 Methodological Framework and Workflow 39
3.5 Sensors-to-synthesis Workflow of Generative Visual Systems 40
3.6 Generative Models and Edge AI for Visual Synthesis 40
3.7 Applications of Edge-AI-driven Generative Visual Systems 42
3.8 Challenges and future directions 43
3.9 Conclusion 44
4 Detecting AI-generated Images in the Social Media Era: A Deep Learning Approach with GenReal Dataset 47
Akhil Sibi, Deepika Pantola, and Madhuri Gupta
4.1 Introduction 47
4.2 Literature Review 48
4.3 Methodology 49
4.4 Results 51
4.5 Conclusion and Future Scope 54
5 Raindrop Removal in Images and Videos Using Generative AI: A Survey 59
Mohd. Aquib Ansari, Vijay Dhote, Sonulal, Shahnawaz Ahmad, and Jiyaul Mustafa
5.1 Introduction 59
5.2 Background and Preliminaries 60
5.3 Generative AI Approaches for Raindrop Removal 62
5.4 Datasets and Evaluation Metrics 64
5.5 Applications 66
5.6 Challenges and Open Issues 68
5.7 Future Directions 69
5.8 Conclusion 70
6 A Transfer Learning Baseline and a GAN-augmentation Perspective for MRI-based Alzheimer's Disease Detection 73
Subiya Zaidi, Arvind Mewada, and Kapil Juneja
6.1 Introduction 73
6.2 Related Work 75
6.3 Materials and Methods 77
6.4 Results 80
6.5 Discussion 81
6.6 Conclusion 84
7 Advanced Foundations and Future Trends in Generative AI for Visual Media 89
Shwetang Dubey, Greetta Pinheiro, Reetu Singh, Mohd. Aquib Ansari, and Lalit Kumar
7.1 Context and Advanced Foundations 89
7.2 Technology Landscape and Mathematical Formulations for Visual Synthesis 90
7.3 Model Trajectories and Scaling Strategies for Visual Synthesis 94
7.4 Evaluation Protocols, Benchmarks, Robustness, and Alignment for Visual Media 96
7.5 Systems Efficiency, Economics, and Deployment for Visual Synthesis 98
7.6 Applications and Translational Pathways for Visual Media 101
7.7 Open Problems and Research Agenda for Visual Synthesis 103
7.8 Conclusion and Outlook for Visual Synthesis 105
8 High-resolution GAN Augmentation with Ensemble CNN Models for Accurate Skin Cancer Detection 109
Amit D. Joshi, Ananya Patil, Niruppreet Kour, Parth Vora, and Tamizharasan P. S
8.1 Introduction 109
8.2 Literature Review 110
8.3 Proposed Methodology 112
8.4 Experimental Setup 114
8.5 Results and Discussion 115
8.6 Conclusion and Future Scope 118
9 Content-aware Convolutional VAE for Anime Face Synthesis 123
Lalit Kumar, Bhupchand Kumar, Shahnawaz Ahmad, Mohd. Aquib Ansari, and Greetta Pinheiro
9.1 Introduction 123
9.2 Related Work 126
9.3 Proposed Model: Content-aware CNN-VAE 128
9.4 Experimental Setup 130
9.5 Results and Analysis 131
9.6 Conclusion 133
10 GEN-HAR: Generative Diffusion Learning for Human Activity Recognition 135
Roshni Singh, Ataus Samad, Abhilasha Sharma, Vandana Bhatia, and Abdul Aleem
10.1 Introduction 135
10.2 Related Work 136
10.3 Proposed Method: GEN-HAR 137
10.4 Experimental Analysis 138
10.5 Conclusion 142
11 Hybrid Neural Networks for Robust Deepfake Detection: Integrating CNN-RNN and Residual Attention Architectures 147
Rupesh Kumar Dewang, Arvind Mewada, Jamvant Omkar, Ayshwarya Jaiswal, and Nagendra Singh
11.1 Introduction 147
11.2 Related Work 148
11.3 Problem Statement 149
11.4 Proposed Work 150
11.5 Experiments and Results 153
11.6 Conclusion and Future Work 160
References 161
Index 163