{"product_id":"deep-learning-to-see-towards-new-foundations-of-computer-vision-9783030909864","title":"Deep Learning to See: Towards New Foundations of Computer Vision","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eThe recent progress in computer vision is attributed to deep learning, but this work questions the scientific progress and proposes investigating vision within the framework of information-based laws of nature. It highlights fundamental questions about vision that remain unanswered and encourages the exploration of appropriate learning theories considering the spatiotemporal nature of the visual signal. The text is suitable for graduate and advanced undergraduate students in computer science, computational neuroscience, physics, and related disciplines. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 105 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 27 April 2022\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer Nature Switzerland AG\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThe remarkable advancements in computer vision over the past few years have been largely attributed to the powerful combination of deep learning, fueled by the vast availability of labeled data, and the rapid growth of the GPU paradigm. While many experts subscribe to this viewpoint, this work aims to critically examine the purported scientific progress in the field and propose an alternative perspective by investigating vision within the framework of information-based laws of nature.\u003cbr\u003e\u003cbr\u003eThis work raises fundamental questions about vision that remain largely unexplored, leading the reader on a captivating journey filled with novel challenges that resonate with the foundations of machine learning. The central thesis proposed is that for a deeper understanding of visual computational processes, it is essential to look beyond the limitations of general-purpose machine learning algorithms and focus on developing appropriate learning theories that account for the spatiotemporal nature of the visual signal.\u003cbr\u003e\u003cbr\u003eBy offering a fresh perspective and challenging established beliefs, this text serves as a catalyst for inspiring and stimulating critical reflection and discussion. It is designed to be accessible to readers with no prior advanced technical knowledge, making it an ideal companion for classic textbooks on computer vision. By providing a comprehensive overview of the current state of the art, open problems, and potential solutions, this text will be of immense benefit to graduate and advanced undergraduate students in computer science, computational neuroscience, physics, and other related disciplines.\u003cbr\u003e\u003cbr\u003eIn conclusion, the remarkable progress in computer vision has been driven by the convergence of deep learning, large datasets, and GPU technology. While this perspective has contributed significantly to our understanding of vision, it is important to challenge the status quo and explore alternative viewpoints. By investigating vision within the framework of information-based laws of nature, we can uncover new insights and pave the way for innovative solutions that will shape the future of this field.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 197g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 235 x 155 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9783030909864\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2022\u003c\/p\u003e","brand":"Alessandro Betti,Marco Gori,Stefano Melacci","offers":[{"title":"Paperback \/ softback","offer_id":44102908543226,"sku":"9783030909864","price":46.96,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1662158055955_book.jpg?v=1662313446","url":"https:\/\/shulphink.com\/products\/deep-learning-to-see-towards-new-foundations-of-computer-vision-9783030909864","provider":"Shulph Ink","version":"1.0","type":"link"}