Advanced Methods and Deep Learning in Computer Vision

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

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  • Author : E. R. Davies
  • Publisher : Academic Press
  • Pages : 550 pages
  • ISBN : 0128221496
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKAdvanced Methods and Deep Learning in Computer Vision

Advanced Methods and Deep Learning in Computer Vision

Advanced Methods and Deep Learning in Computer Vision
  • Author : E. R. Davies,Octavia Camps,Matthew Turk
  • Publisher : Academic Press
  • Release : 01 October 2021
GET THIS BOOKAdvanced Methods and Deep Learning in Computer Vision

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

Applications of Advanced Machine Intelligence in Computer Vision and Object Recognition: Emerging Research and Opportunities

Applications of Advanced Machine Intelligence in Computer Vision and Object Recognition: Emerging Research and Opportunities
  • Author : Chakraborty, Shouvik,Mali, Kalyani
  • Publisher : IGI Global
  • Release : 13 March 2020
GET THIS BOOKApplications of Advanced Machine Intelligence in Computer Vision and Object Recognition: Emerging Research and Opportunities

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 development of digital imaging, yet proper research on the applications of these advancing technologies is lacking. Applications of Advanced Machine Intelligence in Computer Vision and Object Recognition: Emerging Research and

Deep Learning in Computer Vision

Deep Learning in Computer Vision
  • Author : Mahmoud Hassaballah,Ali Ismail Awad
  • Publisher : CRC Press
  • Release : 23 March 2020
GET THIS BOOKDeep Learning in Computer Vision

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 topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community. The book covers a broad scope of topics in deep learning concepts and applications such

Deep Learning in Computer Vision

Deep Learning in Computer Vision
  • Author : Mahmoud Hassaballah,Ali Ismail Awad
  • Publisher : CRC Press
  • Release : 23 March 2020
GET THIS BOOKDeep Learning in Computer Vision

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 topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community. The book covers a broad scope of topics in deep learning concepts and applications such

Challenges and Applications for Implementing Machine Learning in Computer Vision

Challenges and Applications for Implementing Machine Learning in Computer Vision
  • Author : Kashyap, Ramgopal,Kumar, A.V. Senthil
  • Publisher : IGI Global
  • Release : 04 October 2019
GET THIS BOOKChallenges and Applications for Implementing Machine Learning in Computer Vision

Machine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognition, big data collection, and image processing. There is a need for research that seeks to understand the development and efficiency of current methods that enable machines to see. Challenges and Applications for Implementing Machine Learning in Computer Vision is

Deep Learning for Vision Systems

Deep Learning for Vision Systems
  • Author : Mohamed Elgendy
  • Publisher : Manning Publications
  • Release : 10 November 2020
GET THIS BOOKDeep Learning for Vision Systems

How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition. Summary Computer vision is central to many leading-edge innovations, including self-driving cars, drones, augmented reality, facial recognition, and much, much more. Amazing new computer

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch
  • Author : V Kishore Ayyadevara,Yeshwanth Reddy
  • Publisher : Packt Publishing Ltd
  • Release : 27 November 2020
GET THIS BOOKModern Computer Vision with PyTorch

Starting from the basics of neural networks, this book covers over 50 applications of computer vision and helps you to gain a solid understanding of the theory of various architectures before implementing them. Each use case is accompanied by a notebook in GitHub with ready-to-execute code and self-assessment questions.

Mastering Computer Vision with TensorFlow 2.x

Mastering Computer Vision with TensorFlow 2.x
  • Author : Krishnendu Kar
  • Publisher : Packt Publishing Ltd
  • Release : 15 May 2020
GET THIS BOOKMastering Computer Vision with TensorFlow 2.x

Apply neural network architectures to build state-of-the-art computer vision applications using the Python programming language Key Features Gain a fundamental understanding of advanced computer vision and neural network models in use today Cover tasks such as low-level vision, image classification, and object detection Develop deep learning models on cloud platforms and optimize them using TensorFlow Lite and the OpenVINO toolkit Book Description Computer vision allows machines to gain human-level understanding to visualize, process, and analyze images and videos. This book

Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches

Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches
  • Author : Chiranji Lal Chowdhary,Mamoun Alazab,Ankit Chaudhary,Saqib Hakak,Thippa Reddy
  • Publisher : Unknown Publisher
  • Release : 26 November 2021
GET THIS BOOKComputer Vision and Recognition Systems Using Machine and Deep Learning Approaches

This edited book covers the state-of-the-art of academic and industry advanced research in the fields of computer vision and recognition methods, technologies and applications. The first part introduces fundamentals and concepts; the second covers computer vision and recognition methodologies and technologies, and the last part focuses on real world applications using machine and deep learning algorithms.

Machine Learning in Computer Vision

Machine Learning in Computer Vision
  • Author : Nicu Sebe,Ira Cohen,Ashutosh Garg,Thomas S. Huang
  • Publisher : Springer Science & Business Media
  • Release : 30 March 2006
GET THIS BOOKMachine Learning in Computer Vision

The goal of this book is to address the use of several important machine learning techniques into computer vision applications. An innovative combination of computer vision and machine learning techniques has the promise of advancing the field of computer vision, which contributes to better understanding of complex real-world applications. The effective usage of machine learning technology in real-world computer vision problems requires understanding the domain of application, abstraction of a learning problem from a given computer vision task, and the

Computer Vision

Computer Vision
  • Author : Simon J. D. Prince
  • Publisher : Cambridge University Press
  • Release : 18 June 2012
GET THIS BOOKComputer Vision

A modern treatment focusing on learning and inference, with minimal prerequisites, real-world examples and implementable algorithms.

Deep Learning

Deep Learning
  • Author : Ian Goodfellow,Yoshua Bengio,Aaron Courville
  • Publisher : MIT Press
  • Release : 10 November 2016
GET THIS BOOKDeep Learning

An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts.

Machine Vision

Machine Vision
  • Author : E. R. Davies
  • Publisher : Elsevier
  • Release : 22 December 2004
GET THIS BOOKMachine Vision

In the last 40 years, machine vision has evolved into a mature field embracing a wide range of applications including surveillance, automated inspection, robot assembly, vehicle guidance, traffic monitoring and control, signature verification, biometric measurement, and analysis of remotely sensed images. While researchers and industry specialists continue to document their work in this area, it has become increasingly difficult for professionals and graduate students to understand the essential theory and practicalities well enough to design their own algorithms and systems. This

Deep Learning for Computer Vision

Deep Learning for Computer Vision
  • Author : Rajalingappaa Shanmugamani
  • Publisher : Packt Publishing Ltd
  • Release : 23 January 2018
GET THIS BOOKDeep Learning for Computer Vision

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 detection, image classification, similarity learning, image captioning, and more Includes tips on optimizing and improving the performance of your models under various constraints Book Description Deep learning has shown its