The book comprehensively covers a wide range of evolutionary computer vision methods and applications, feature selection and extraction for training and classification, and metaheuristic algorithms in image processing. It further discusses optimized image segmentation, its analysis, pattern recognition, and object detection.
Features:
- Discusses machine learning-based analytics such as GAN networks, autoencoders, computational imaging, and quantum computing
- Covers deep learning algorithms in computer vision
- Showcases novel solutions such as multi-resolution analysis in imaging processing, and metaheuristic algorithms for tackling challenges associated with image processing
- Highlight optimization problems such as image segmentation and minimized feature design vector
- Presents platform and simulation tools for image processing and segmentation
The book aims to get the readers familiar with the fundamentals of computational intelligence as well as the recent advancements in related technologies like smart applications of digital images, and other enabling technologies from the context of image processing and computer vision. It further covers important topics such as image watermarking, steganography, morphological processing, and optimized image segmentation. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in fields including electrical engineering, electronics, communications engineering, and computer engineering.
Betal enkelt med kort, Klarna, Apple Pay eller Google Pay. Ikke fornøyd? Du har alltid 14 dagers angrerett. Les mer i våre vilkår. Har du spørsmål, send oss en e-post på hello@memmo.org.
Memmo gjør det enklere å studere – uansett hvor du er i verden. Hos oss samler du pensumbøker og smarte studieverktøy på ett og samme sted: sammendrag, quizer, podkaster og flashcards. Og så Ted, din studiekompis som svarer på alt du lurer på. Over 50 000 studenter studerer allerede her – bygget for at du skal lære raskere og stresse mindre.