{"product_id":"9783031949685","title":"Advances in Computer Vision and Pattern Recognition: Pre-training, Prompting, and Applications","description":"\u003ch1\u003eAdvances in Computer Vision and Pattern Recognition: Pre-training, Prompting, and Applications\u003c\/h1\u003e \u003ch2\u003eZhou, Kaiyang; Liu, Ziwei; Gao, Peng\u003c\/h2\u003e \u003cp\u003e\u003c\/p\u003e\u003cp\u003eThe rapid progress in the field of large multimodal foundation models, especially vision-language models, has dramatically transformed the landscape of machine learning, computer vision, and natural language processing. These powerful models, trained on vast amounts of multimodal data mixed with images and text, have demonstrated remarkable capabilities in tasks ranging from image classification and object detection to visual content generation and question answering. This book provides a comprehensive and up-to-date exploration of large vision-language models, covering the key aspects of their pre-training, prompting techniques, and diverse real-world computer vision applications. It is an essential resource for researchers, practitioners, and students in the fields of computer vision, natural language processing, and artificial intelligence.\u003c\/p\u003e\n\u003cdiv class=\"relative\"\u003e\n\u003cdiv class=\"prose text-pretty dark:prose-invert inline leading-normal break-words min-w-0 [word-break:break-word]\"\u003e\n\u003cp class=\"my-0\"\u003e\u003cem\u003e\u003cspan style=\"font-size: 11.0pt; font-family: 'Calibri',sans-serif; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;\"\u003eLarge Vision-Language Models\u003c\/span\u003e\u003c\/em\u003e begins by exploring the fundamentals of large vision-language models, covering architectural designs, training techniques, and dataset construction methods. It then examines prompting strategies and other adaptation methods, demonstrating how these models can be effectively fine-tuned to address a wide range of downstream tasks. The final section focuses on the application of vision-language models across various domains, including open-vocabulary object detection, 3D point cloud processing, and text-driven visual content generation and manipulation.\u003c\/p\u003e\n\u003cp class=\"my-0\"\u003eBeyond the technical foundations, the book explores the wide-ranging applications of vision-language models (VLMs), from enhancing image recognition systems to enabling sophisticated visual content generation and facilitating more natural human-machine interactions. It also addresses key challenges in the field, such as feature alignment, scalability, data requirements, and evaluation metrics. By providing a comprehensive roadmap for both newcomers and experts, this book serves as a valuable resource for understanding the current landscape, limitations, and future directions of VLMs, ultimately contributing to the advancement of artificial intelligence.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"absolute\"\u003e\n\u003cdiv class=\"bg-offset dark:bg-offsetDark rounded-lg shadow-lg\"\u003e\n\u003cdiv class=\"flex items-center min-w-0 font-medium gap-1.5 justify-center\"\u003e \u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2025-08-31\u003c\/p\u003e \u003cp\u003eFormat: Hardcover\u003c\/p\u003e \u003cp\u003eISBN-13: 9783031949685\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-3-031-94969-2\u003c\/p\u003e \u003cp\u003eDimensions: 235cm x155cm\u003c\/p\u003e \u003cp\u003ePages: 429\u003c\/p\u003e ","brand":"Springer Nature Switzerland","offers":[{"title":"Default Title","offer_id":44341125939340,"sku":"9783031949685","price":179.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9783031949685.jpg?v=1779936289","url":"https:\/\/lateknightbooks.com\/products\/9783031949685","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}