Название: Recent Trends in Image and Signal Processing in Computer Vision Автор: Shruti Jain, Sudip Paul
Издательство: Springer
Год: 2020
Страниц: 293
Язык: английский
Формат: pdf (true)
Размер: 13,0 MB
This book highlights recent advances and emerging technologies that utilize computational intelligence in signal processing, computing, imaging science, artificial intelligence, and their applications. It covers all branches of artificial intelligence and machine learning that are based on computation at some level, e.g. artificial neural networks, evolutionary algorithms, fuzzy systems, and automatic medical identification systems. Exploring recent trends in research and applications, the book offers a valuable resource for professors, researchers, and engineers alike.
Computer vision is a recently emerging area in fundamental and applied research, exploiting a number of advanced information processing technologies that mainly embody neural networks, fuzzy logic, machine learning, and evolutionary computation. The “Recent Trends in Image/Signal Processing in Computer Vision” book encompasses all branches of artificial intelligence and machine learning which are based on computation at some level such as artificial neural networks, evolutionary algorithms, fuzzy systems, and medical automatic identification intelligence system. It presents the latest research being conducted on diverse topics in intelligence technologies with the goal of advancing knowledge and applications in this rapidly evolving field.
Road traffic management is of importance to traffic engineers and road users. Several attempts at the management of traffic and traffic congestion have come short of reaching the desired goals because of the lack of suitable techniques for allocating time to various intersecting traffic routes. A suitable model for analyzing road network congestion and the concept of busy-hour from telecommunication theory can fulfill the need of the hour. To overcome this, algorithm is developed in Microsoft Studio Developer Platform with Fortran. The numerical results obtained in this show that the telecommunications approach can be used to indicate the state of congestion on a traffic route.
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