Advanced Methods and Deep Learning in Computer Vision

Advanced Methods and Deep Learning in Computer Vision

Author: E. R. Davies

Publisher: Academic Press

ISBN: 9780128221495

Category: Computers

Page: 582

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Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emerged during the past 5–10 years. The book provides clear explanations of principles and algorithms supported with applications. Topics covered include machine learning, deep learning networks, generative adversarial networks, deep reinforcement learning, self-supervised learning, extraction of robust features, object detection, semantic segmentation, linguistic descriptions of images, visual search, visual tracking, 3D shape retrieval, image inpainting, novelty and anomaly detection. This book provides easy learning for researchers and practitioners of advanced computer vision methods, but it is also suitable as a textbook for a second course on computer vision and deep learning for advanced undergraduates and graduate students. Provides an important reference on deep learning and advanced computer methods that was created by leaders in the field Illustrates principles with modern, real-world applications Suitable for self-learning or as a text for graduate courses
Advanced Methods and Deep Learning in Computer Vision
Language: en
Pages: 582
Authors: E. R. Davies, Matthew Turk
Categories: Computers
Type: BOOK - Published: 2021-11-09 - Publisher: Academic Press

Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emerged during the past 5–10 years. The book provides clear explanations of principles and algorithms supported with applications. Topics covered include machine learning, deep learning networks, generative adversarial networks,
Deep Learning for Computer Vision
Language: en
Pages: 310
Authors: Rajalingappaa Shanmugamani
Categories: Computers
Type: BOOK - Published: 2018-01-23 - Publisher: Packt Publishing

Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks Key Features Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision Combine the power of Python, Keras, and TensorFlow to build deep learning models for object
Deep Learning in Computer Vision
Language: en
Pages: 322
Authors: Mahmoud Hassaballah, Ali Ismail Awad
Categories: Computers
Type: BOOK - Published: 2020-03-23 - Publisher: CRC Press

Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions to several image-related problems that had long remained unsolved or partially addressed. This book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific
Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction
Language: en
Pages: 1221
Authors: Khosrow-Pour, D.B.A., Mehdi
Categories: Computers
Type: BOOK - Published: 2018-09-28 - Publisher: IGI Global

As modern technologies continue to develop and evolve, the ability of users to adapt with new systems becomes a paramount concern. Research into new ways for humans to make use of advanced computers and other such technologies through artificial intelligence and computer simulation is necessary to fully realize the potential
Applications of Advanced Machine Intelligence in Computer Vision and Object Recognition: Emerging Research and Opportunities
Language: en
Pages: 271
Authors: Chakraborty, Shouvik, Mali, Kalyani
Categories: Computers
Type: BOOK - Published: 2020-03-13 - Publisher: IGI Global

Computer vision and object recognition are two technological methods that are frequently used in various professional disciplines. In order to maintain high levels of quality and accuracy of services in these sectors, continuous enhancements and improvements are needed. The implementation of artificial intelligence and machine learning has assisted in the