This guide goes step-by-step journey from the fundamentals of Generative AI to advanced applications. It unravels the complexities of generative models, delves into such key techniques as GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders), and provides a foundation to understand the underlying principles.
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 GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders), providing a solid foundation for readers to understand the underlying principles. The book:
- 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 theory, this book offers hands-on insights into real-world applications of Generative AI. From 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.
1. Generative AI and Creativity: An Overview
2. Understanding Creativity
Using Generative AI: 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 GenAI
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 Basal Cell Carcinoma: Designing a
Generative AI Framework for Accurate Basal Cell Carcinoma Image
Classification Using EfficientNet and Transfer Learning
9. Generative
AIDriven 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 Frameworks and Tools for Generation of
Multi-Perspective Contents
13. Comprehensive Understanding of Evaluating and
Testing Generative Models
14. Metrics, Tools and 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 Education 4.0
20. Generative AI
Challenges and Future Directions
21. Comparative Analysis of Transformer
Models for Stack Overflow Question Quality Classification
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.
