Bangio – Computer Vision

Libro adottato a Siena, a.a. 2026/2027 · 1 canale

«Bangio – Computer Vision» è adottato per Digital Image Processing dal prof. Alessandro Mecocci (Artificial Intelligence and Automation Engineering – sede di Siena – Siena).

Come lo indica il docente: Recommended Books 1) R. Szeliski, “Computer Vision: Algorithms and Applications, 2nd ed.”, Springer 2022 2) David A. Forsyth and Jean Ponce, "Computer Vision: A Modern Approach", Pearson Education Limited, 2012. 3) John C. Russ, The Image Processing Handbook 7th Edition, CRC Press, 2016 4) E. R. Davies, "Computer Vision: Principles, Algorithms, Applications, Learning", ACADEMIC PRESS, 2018 5) I. Goodfellow, Y. Bangio, "Deep Learning", The MIT Press, 2016 6) M. Elgendy, “Deep Learning for Vision Systems”, Manning Publications Co., 2020 7) L. Lin, P. Luo, W. Zuo Eds., "Deep Learning for Human Centric Visual Analysis", Springer Nature Singapore Pte Ltd. 2020 8) X. Jiang, A. Hadid, Y. Pang, E. Granger Eds., "Deep Learning in Object Detection and Recognition", Springer Nature Singapore Pte Ltd. 2019 9) Olivier Faugeras, "Three Dimensional Computer Vision", MIT Press, 1993 10) J. F. Peters, "Foundations of Computer Vision: Computational Geometry, Visual Image Structures and Object Shape Detection", Springer Nature, 2018 11) L. Lu, X. Wang, G. Carneiro, L. Yang, "Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics", Springer Nature Switzerland AG 2019 Other interesting readings 1) Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins, "Digital Image Processing Using MATLAB". 2) S. Mallat , "A Wavelet Tour of Signal Processing", Academic Press, 1999 3) H. Venkateswara, S. Panchanathan Eds., "Domain Adaptation in Computer Vision With Deep Learning", Springer Nature, Switzerland, AG 2020 4) Y. Ma, J. Tang, "Deep Learning on Graphs", Cambridge University Press, 2021 5) M. Leordeanu, "Unsupervised Learning in Space and Time: A Modern Approach for Computer Vision using Graph-based Techniques and Deep Neural Networks", Springer Nature Switzerland, AG 2020 6) Z. Wang, "Deep Learning Through Sparse and Low-Rank Modeling", Academic Press, 2019 7) X. Li, M. Wu, Z. Chen, L. Zhang Eds., "Deep Learning for Human Activity Recognition: Second International Workshop, DL-HAR 2020", Springer Nature Singapore Pte Ltd. 2021 8) S. Ansari, "Building Computer Vision Applications Using Artificial Neural Networks", Apress, 2020 9) S. Holden, "Computer Vision: Advanced Techniques and Applications", Clanrye Intl, 2019 10) M. Hassaballah, "Deep Learning in Computer Vision: Principles and Applications", CRC Press Taylor & Francis Group, New York, 2020 11) H. Dong, Z. Ding, S. Zhang, "Deep Reinforcement Learning: Fundamentals, Research and Applications ", Springer Nature Singapore Pte Ltd. 2020 12) N. Singh, P. Ahuja, "Fundamentals of Deep Learning and Computer Vision", BPB BOOK CENTRE, 2020 13) S. Khan, H. Rahmani, S. A. Shah, M. Bennamoun, "A Guide to Convolutional Neural Networks for Computer Vision", Morgan & Claypool 2018

Chi lo adotta

• Digital Image Processing – Prof. Alessandro Mecocci (canale unico)Artificial Intelligence and Automation Engineering – sede di Siena · Laurea magistrale (LM-32) · 1º anno · 1º semestre · Intelligent Sistems · 6 CFU

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