Overview

Generative AI and Creativity: From Theory to Practice is an immersive exploration into the revolutionary domain of generative artificial intelligence. It takes a step-by-step journey starting with the fundamentals of generative AI and progressing to advanced applications. The book unravels the complexities of generative models, delving into key techniques such as generative adversarial networks (GANs) and variational autoencoders (VAE)s, providing a solid foundation for readers to understand the underlying principles. FEATURES • Explores the collaboration between humans and AI in creative processes • Examines generative art movements, graphic design applications, and artist-AI collaborations • Defines creativity in AI, by showcasing case studies and discussing ethical considerations Moving beyond creative content generation in art and music to practical implementations in industries like healthcare and finance, the book showcases the versatility and transformative potential of generative AI across diverse domains. Readers will gain practical skills through coding examples, case studies, and collaborative projects, empowering them to integrate generative AI into their own work. The book is enriched with stories of innovation, featuring pioneers who have leveraged generative AI to push the boundaries of creativity. Ethical considerations and the societal impact of generative AI are also explored to foster a holistic understanding of the technology.

Full Product Details

Author:   Elakkiya Rajasekar ,  Subramaniyaswamy V
Publisher:   Taylor & Francis Ltd
Imprint:   Auerbach
Weight:   0.850kg
ISBN:  

9781032867373

ISBN 10:   103286737
Pages:   347
Publication Date:   24 November 2025
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Not yet available  
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Table of Contents

1. Generative AI and Creativity: An Overview 2. Understanding Creativity Using Generative AI: An In-Depth Analysis 3. Harmonizing Tradition and Innovation: Computational Strategies for Preserving Thanjavur Paintings from Generative AI 4. Creation and Analysis of Sculptures Using the Principles of Generative AI 5. An Automated Image Style Transfer Framework Using Gen AI Algorithm 6. Human-AI Collaboration with Decision Control and Adaptive Trust for Enhancing User Perceptions 7. Applications of Generative AI in Gaming and Virtual Environments 8. EffiTrans BCC: Designing a Generative AI Framework for Accurate Basal Cell Carcinoma Image Classification Using EfficientNet and Transfer Learning 9. Generative AI-Driven Music Genre Classification: Unlocking Creativity and Innovation in Automated Audio Analysis 10. Image-Based Analysis of Parkinson's Disease Using Generative Artificial Intelligence Algorithms 11. Harnessing Generative AI Tools and Techniques: Beyond Algorithms for a Smarter Future 12. An Exploration of Generative AI (GAI) Frameworks and Tools for Generation of Multi-Perspective Contents 13. Comprehensive Understanding of Evaluating and Testing Generative Models 14. Metrics, Tools & Challenges for Assessing Generative Models 15. Rise of Generative AI: Exploring Its Impact on Creative Industries 16. Impact of Commercial Applications on GenAI with Its Evolving Landscape 17. AI in Academic Environments: A Study of Perspectives and Practices 18. Generative AI: A Personalized and Ubiquitous Tutor 19. Integration of Generative AI: An Advent of Educational 4.0 20. Generative AI: Challenges and Future Directions 21. Comparative Analysis of Transformer Models for Stack Overflow Question Quality Classification

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Author Information

Dr. Elakkiya Rajasekar is an assistant professor of computer science in the Department of Computer Science, Birla Institute of Technology and Science Pilani, Dubai Campus. She specializes in generative AI and computer vision, applied to language technologies, healthcare, assistive systems, and other interdisciplinary domains. She has led 16 extra-mural funded research projects supported by agencies, including DST-RFBR, DRDO, and Royal Society UK. She serves as chair of the Dubai ACM-W Chapter and vice president of the Dubai ACM Chapter and is recognized among the Top 2% Scientists by Stanford. Dr. Subramaniyaswamy V is currently working as a professor in the School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India. In total, he has 21 years of experience in academia and research. He has published papers in reputed international journals and conferences and filed multiple patents. His technical competencies lie in recommender systems, artificial intelligence, reinforcement learning, big data analytics, and cognitive analytics.

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