Machine Vision and Augmented Intelligence, Kumar Singh

Автор: Bajpai Manish Kumar, Kumar Singh Koushlendra, Giakos George
Название: Machine Vision and Augmented Intelligence--Theory and Applications: Select Proceedings of Mai 2021
ISBN: 9811650772 ISBN-13(EAN): 9789811650772
Издательство: Springer
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Цена: 204970.00 T
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Описание: Chapter 01: Modelling of Disease Transformation.- Chapter 02: Epidemic Forecast.- Chapter 03: COVID-19: Theory and practice.- Chapter 04: Image Processing and Computer Vision.- Chapter 05: Augmented Intelligence: Theory and Applications.- Chapter 06: Soft Computing: Theory and Applications.- Chapter 07: Deep Learning: Theory and Applications.- Chapter 08: Image Reconstruction.- Chapter 09: Artificial Intelligence in Healthcare.- Chapter 10: Brain Computer Interface.- Chapter 11: Cyber Security and Social Network Analysis.- Chapter 12: Natural Language Processing.- Chapter 13: Cryptography and Image Security.

Автор: Ramgopal Kashyap, A.V. Senthil Kumar
Название: Challenges and Applications for Implementing Machine Learning in Computer Vision
ISBN: 1799801837 ISBN-13(EAN): 9781799801832
Издательство: Mare Nostrum (Eurospan)
Цена: 173190.00 T
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Описание: 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 a collection of innovative research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual processing. Highlighting a wide range of topics such as video segmentation, object recognition, and 3D modelling, this publication is ideally designed for computer scientists, medical professionals, computer engineers, information technology practitioners, industry experts, scholars, researchers, and students seeking current research on the utilization of evolving computer vision techniques.

Автор: Julio C. Rodriguez-Quinonez, Oleg Sergiyenko, Wendy Flores-Fuentes
Название: Examining Optoelectronics in Machine Vision and Applications in Industry 4.0
ISBN: 1799865231 ISBN-13(EAN): 9781799865230
Издательство: Mare Nostrum (Eurospan)
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Описание: Focuses on the examination of emerging technologies for the design, fabrication, and implementation of optoelectronic sensors, devices, and systems in a machine vision approach to support industrial, commercial, and scientific applications.

Автор: Rajshree Srivastava, Pradeep Kumar Mallick, Siddha
Название: Computational Intelligence for Machine Learning and Healthcare Informatics
ISBN: 3110647826 ISBN-13(EAN): 9783110647822
Издательство: Walter de Gruyter
Цена: 136310.00 T
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Описание: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS
By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.

Автор: Roberto Cipolla; Sebastiano Battiato; Giovanni Mar
Название: Machine Learning for Computer Vision
ISBN: 3642446868 ISBN-13(EAN): 9783642446863
Издательство: Springer
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Цена: 113180.00 T
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Описание: Collecting articles covering talks and tutorials from the latest session of the International Computer Vision Summer School (ICVSS), this book offers a thorough exploration of current progress in the science and technology of making machines that see.

Автор: Marzena Kryszkiewicz; Sanghamitra Bandyopadhyay; H
Название: Pattern Recognition and Machine Intelligence
ISBN: 3319199404 ISBN-13(EAN): 9783319199405
Издательство: Springer
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Цена: 74530.00 T
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Описание: This book constitutes the proceedings of the 6th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2015, held in Warsaw, Poland, in June/July 2015. The total of 53 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 90 submissions. They were organized in topical sections named: foundations of machine learning; image processing; image retrieval; image tracking; pattern recognition; data mining techniques for large scale data; fuzzy computing; rough sets; bioinformatics; and applications of artificial intelligence.

Автор: Takashi Matsuyama; Vincent Shang-Shouq Hwang
Название: SIGMA
ISBN: 030643301X ISBN-13(EAN): 9780306433016
Издательство: Springer
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Цена: 139710.00 T
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Описание: It has long been a dream to realize machines with flexible visual perception capability. Research on digital image processing by computers was initiated about 30 years ago, and since then a wide variety of image processing algorithms have been devised. Using such image processing algorithms and advanced hardware technologies, many practical ma- chines with visual recognition capability have been implemented and are used in various fields: optical character readers and design chart readers in offices, position-sensing and inspection systems in factories, computer tomography and medical X-ray and microscope examination systems in hospitals, and so on. Although these machines are useful for specific tasks, their capabilities are limited. That is, they can analyze only simple images which are recorded under very carefully adjusted photographic conditions: objects to be recognized are isolated against a uniform background and under well-controlled artificial lighting. In the late 1970s, many image understanding systems were de- veloped to study the automatic interpretation of complex natural scenes. They introduced artificial intelligence techniques to represent the knowl- edge about scenes and to realize flexible control structures. The first author developed an automatic aerial photograph interpretation system based on the blackboard model (Naga1980). Although these systems could analyze fairly complex scenes, their capabilities were still limited; the types of recognizable objects were limited and various recognition vii viii Preface errors occurred due to noise and the imperfection of segmentation algorithms.

Автор: Vipin Kumar; P.S. Gopalakrishnan; Laveen N. Kanal
Название: Parallel Algorithms for Machine Intelligence and Vision
ISBN: 1461279941 ISBN-13(EAN): 9781461279945
Издательство: Springer
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Цена: 111790.00 T
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Описание: Recent research results in the area of parallel algorithms for problem solving, search, natural language parsing, and computer vision, are brought together in this book.

Автор: Takashi Matsuyama; Vincent Shang-Shouq Hwang
Название: SIGMA
ISBN: 1489908692 ISBN-13(EAN): 9781489908698
Издательство: Springer
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Цена: 93160.00 T
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Автор: Salman Khan, Hossein Rahmani, Syed Afaq Ali Shah, Mohammed Bennamoun
Название: A Guide to Convolutional Neural Networks for Computer Vision
ISBN: 1681732785 ISBN-13(EAN): 9781681732787
Издательство: Mare Nostrum (Eurospan)
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Цена: 102570.00 T
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Описание: Computer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding performance in these state-of-the-art visual recognition tasks and systems. As a result, CNNs now form the crux of deep learning algorithms in computer vision.This self-contained guide will benefit those who seek to both understand the theory behind CNNs and to gain hands-on experience on the application of CNNs in computer vision. It provides a comprehensive introduction to CNNs starting with the essential concepts behind neural networks: training, regularization, and optimization of CNNs. The book also discusses a wide range of loss functions, network layers, and popular CNN architectures, reviews the different techniques for the evaluation of CNNs, and presents some popular CNN tools and libraries that are commonly used in computer vision. Further, this text describes and discusses case studies that are related to the application of CNN in computer vision, including image classification, object detection, semantic segmentation, scene understanding, and image generation.This book is ideal for undergraduate and graduate students, as no prior background knowledge in the field is required to follow the material, as well as new researchers, developers, engineers, and practitioners who are interested in gaining a quick understanding of CNN models.

Автор: Jennifer Boger, Victoria Young, Jesse Hoey, Tizneem Jiancaro, Alex Mihailidis
Название: Zero-Effort Technologies: Considerations, Challenges, and Use in Health, Wellness, and Rehabilitation, Second Edition
ISBN: 1681732866 ISBN-13(EAN): 9781681732862
Издательство: Mare Nostrum (Eurospan)
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Цена: 82230.00 T
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Описание: This book introduces zero-effort technologies (ZETs), an emerging class of technologies that require little or no effort from the people who use them. ZETs use advanced computing techniques, such as computer vision, sensor fusion, decision-making and planning, machine learning, and the Internet of Things to autonomously perform the collection, analysis, and application of data about the user and/or his/her context. This book begins with an overview of ZETs, then presents concepts related to their development, including pervasive intelligent technologies and environments, design principles, and considerations regarding use. The book discusses select examples of the latest in ZET development before concluding with thoughts regarding future directions of the field.

Автор: Michael Felsberg
Название: Probabilistic and Biologically Inspired Feature Representations
ISBN: 1681730235 ISBN-13(EAN): 9781681730233
Издательство: Mare Nostrum (Eurospan)
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Описание: Under the title Probabilistic and Biologically Inspired Feature Representations, this text collects a substantial amount of work on the topic of channel representations. Channel representations are a biologically motivated, wavelet-like approach to visual feature descriptors: they are local and compact, they form a computational framework, and the represented information can be reconstructed. The first property is shared with many histogram- and signature-based descriptors, the latter property with the related concept of population codes. In their unique combination of properties, channel representations become a visual Swiss army knife—they can be used for image enhancement, visual object tracking, as 2D and 3D descriptors, and for pose estimation. In the chapters of this text, the framework of channel representations will be introduced and its attributes will be elaborated, as well as further insight into its probabilistic modeling and algorithmic implementation will be given. Channel representations are a useful toolbox to represent visual information for machine learning, as they establish a generic way to compute popular descriptors such as HOG, SIFT, and SHOT. Even in an age of deep learning, they provide a good compromise between hand-designed descriptors and a-priori structureless feature spaces as seen in the layers of deep networks.