Man Luo; Tejas Gokhale; Neeraj Varshney; Yezhou Yang; Chitta Baral Springer International Publishing AG (2024) Saatavuus: Tilaustuote Kovakantinen kirja
Man Ho Au; Siu Ming Yiu; Jin Li; Xiapu Luo; Cong Wang; Aniello Castiglione; Kamil Kluczniak Springer Nature Switzerland AG (2018) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Haixin Duan (ed.); Mourad Debbabi (ed.); Xavier de Carné de Carnavalet (ed.); Xiapu Luo (ed.); Xiaojiang Du (ed.); Man Au Springer (2024) Saatavuus: Tulossa! Pehmeäkantinen kirja
Haixin Duan (ed.); Mourad Debbabi (ed.); Xavier de Carné de Carnavalet (ed.); Xiapu Luo (ed.); Xiaojiang Du (ed.); Man Au Springer (2024) Saatavuus: Tulossa! Pehmeäkantinen kirja
This book provides an extensive examination of state-of-the-art methods in multimodal retrieval, generation, and the pioneering field of retrieval-augmented generation. The work is rooted in the domain of Transformer-based models, exploring the complexities of blending and interpreting the intricate connections between text and images. The authors present cutting-edge theories, methodologies, and frameworks dedicated to multimodal retrieval and generation, aiming to furnish readers with a comprehensive understanding of the current state and future prospects of multimodal AI. As such, the book is a crucial resource for anyone interested in delving into the intricacies of multimodal retrieval and generation. Serving as a bridge to mastering and leveraging advanced AI technologies in this field, the book is designed for students, researchers, practitioners, and AI aficionados alike, offering the tools needed to expand the horizons of what can be achieved in multimodal artificial intelligence.
