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Multimodal Generative AI

This book stands at the forefront of AI research, offering a comprehensive examination of multimodal generative technologies. Readers are taken on a journey through the evolution of generative models, from early neural networks to contemporary marvels like GANs and VAEs, and their transformative app...

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Detalles Bibliográficos
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Singh, Akansha (Editor), Singh, Krishna Kant (Editor)
Formato: Electrónico eBook
Lenguaje:inglés
Publicado: Singapore : Springer Nature Singapore : Imprint: Springer, 2025.
Edición:1st ed. 2025.
Materias:
Image processing > Digital techniques.
Computer vision.
Image processing.
Artificial intelligence.
Natural language processing (Computer science).
Machine learning.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Image Processing.
Computer Vision.
Artificial Intelligence.
Natural Language Processing (NLP).
Machine Learning.
Acceso en línea:https://doi.org/10.1007/978-981-96-2355-6
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Tabla de Contenidos:
  • Chapter 1. Introduction to Multimodal Generative AI
  • Chapter 2. ChatGPT and BERT: Comparative Analysis of Various Natural Language Processing Applications
  • Chapter 3. Large Language Model on Multi-Modal Data
  • Chapter 4. Adaptive Learning Technologies: Navigating the Road from Hype to Reality
  • Chapter 5. Generative Artificial Intelligence in Visual Content: A Review of the Influence on Consumer Perception and Perspective
  • Chapter 6. Text-to-Image Synthesis: Techniques and Applications
  • Chapter 7. Image-to-Text Generation: Bridging Visual and Linguistic Worlds
  • Chapter 8. Sustainability in the Metaverse: Challenges, Implications, and Potential Solutions
  • Chapter 9. Transcendent Artificial Intelligence in Education
  • Chapter 10. Chat GPT in Academia and Research - A Comprehensive Review of Integrating AI in Higher Education
  • Chapter 11. Exploring Multimodal Hate Speech Detection Using Machine Learning and Deep Learning Models
  • Chapter 12. Multimodal Generative AI for People with Disabilities
  • Chapter 13. Single-Modality to Multimodality: The Evolutionary Trajectory of Artificial Intelligence in Integrating Diverse Data Streams for Enhanced Cognitive Capabilities
  • Chapter 14. Interfacing Multimodal AI with IoT: Unlocking New Frontiers.-Chapter 15. Enhancing Safety and Reliability in VANETs for Autonomous Vehicles by M-XAI (Multi Model- Explainable-AI)
  • Chapter 16. Future Directions In Multimodal Genrative AI.

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