BOOKS - Integrating Metaheuristics in Computer Vision for Real-World Optimization Pro...
Integrating Metaheuristics in Computer Vision for Real-World Optimization Problems - Shubham Mahajan, Kapil Joshi, Amit Kant Pandit 2024 PDF Wiley-Scrivener BOOKS
ECO~15 kg CO²

1 TON

Views
47010

Telegram
 
Integrating Metaheuristics in Computer Vision for Real-World Optimization Problems
Author: Shubham Mahajan, Kapil Joshi, Amit Kant Pandit
Year: 2024
Pages: 353
Format: PDF
File size: 16.2 MB
Language: ENG



Pay with Telegram STARS
Book Description: This book provides a comprehensive overview of the current state of computer vision research, including the development of metaheuristics and their applications in real-world optimization problems. The book covers topics such as image processing, feature extraction, object recognition, and scene understanding, as well as the use of machine learning algorithms to improve performance. It also discusses the challenges and limitations of current computer vision systems and outlines potential future directions for the field. Book Outline: 1. Introduction 2. Background and History of Computer Vision 3. Current State of Computer Vision Research 4. Applications of Metaheuristics in Computer Vision 5. Challenges and Limitations of Current Computer Vision Systems 6. Future Directions for Computer Vision Research 7. Conclusion Book Content: 1. Introduction Computer vision has become an essential tool in modern technology, with applications ranging from facial recognition to self-driving cars. However, despite its widespread adoption, there are still significant challenges that need to be addressed to ensure the continued evolution of this technology.
В этой книге представлен всесторонний обзор текущего состояния исследований в области компьютерного зрения, включая разработку метаэвристики и ее приложений в реальных задачах оптимизации. Книга охватывает такие темы, как обработка изображений, извлечение признаков, распознавание объектов и понимание сцены, а также использование алгоритмов машинного обучения для повышения производительности. В нем также обсуждаются проблемы и ограничения современных систем компьютерного зрения и излагаются потенциальные будущие направления для этой области. Структура книги: 1. Введение 2. Предпосылки и история компьютерного зрения 3. Текущее состояние исследований компьютерного зрения 4. Применение метаэвристики в Computer Vision 5. Проблемы и ограничения современных систем компьютерного зрения 6. Будущие направления исследований компьютерного зрения 7. Заключение Содержание книги: 1. Введение Компьютерное зрение стало важным инструментом в современных технологиях, с приложениями от распознавания лиц до беспилотных автомобилей. Однако, несмотря на широкое распространение, все еще существуют значительные проблемы, которые необходимо решить, чтобы обеспечить продолжение эволюции этой технологии.
''

You may also be interested in:

Integrating Metaheuristics in Computer Vision for Real-World Optimization Problems
Integrating Metaheuristics in Computer Vision for Real-World Optimization Problems
Integrating Metaheuristics in Computer Vision for Real-World Optimization Problems
Computer Vision - ACCV 2022: 16th Asian Conference on Computer Vision, Macao, China, December 4-8, 2022, Proceedings, Part IV (Lecture Notes in Computer Science)
Neural Network Computer Vision with OpenCV 5: Build computer vision solutions using Python and DNN module (English Edition)
Neural Network Computer Vision with OpenCV 5 Build computer vision solutions using Python and DNN module
Neural Network Computer Vision with OpenCV 5 Build computer vision solutions using Python and DNN module
Learning OpenCV 5 Computer Vision with Python, Fourth Edition: Tackle computer vision and machine learning with the newest tools, techniques and algorithms
Mastering Computer Vision with PyTorch 2.0 Discover, Design, and Build Cutting-Edge High Performance Computer Vision Solutions with PyTorch 2.0 and Deep Learning Techniques
Computer Vision Object Detection In Adversarial Vision
Computer Vision Object Detection In Adversarial Vision
Metaheuristics for Enterprise Data Intelligence (Advances in Metaheuristics)
Computer Vision - ECCV 2020 Workshops: Glasgow, UK, August 23-28, 2020, Proceedings, Part V (Lecture Notes in Computer Science)
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 22nd Iberoamerican Congress, CIARP 2017, Valparaiso, Chile, November … Notes in Computer Science Book 10657)
Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging: Mathematical Imaging and Vision
Computer Vision
Infrastructure Computer Vision
Fundamentals of Computer Vision
Foundations of Computer Vision
Foundations of Computer Vision
Raspberry Pi Computer Vision Programming
Application of Chaos and Fractals to Computer Vision
Computer Vision Three-dimensional Reconstruction Techniques
3D Computer Vision Foundations and Advanced Methodologies
3D Computer Vision Foundations and Advanced Methodologies
Leveraging Computer Vision to Biometric Applications
Computer Vision: Three-dimensional Reconstruction Techniques
Applications of Computer Vision in Automation and Robotics
Intelligent Systems and Applications in Computer Vision
Intelligent Systems and Applications in Computer Vision
Computer Vision Challenges, Trends, and Opportunities
Leveraging Computer Vision to Biometric Applications
2D Computer Vision:Principles, Algorithms and Applications
Probabilistic Graphical Models for Computer Vision
Intelligent Systems and Applications in Computer Vision
Computer Vision Challenges, Trends, and Opportunities
2D Computer Vision Principles, Algorithms and Applications
Computer Vision Three-dimensional Reconstruction Techniques
Deep Learning for Computer Vision with SAS An Introduction
Image Processing, Computer Vision, and Pattern Recognition