Recent Advances on Memetic Algorithms and its Applications in Image Processing [electronic resource] /
edited by D. Jude Hemanth, B. Vinoth Kumar, G. R. Karpagam Manavalan.
- 1st ed. 2020.
- XIV, 199 p. 69 illus., 45 illus. in color. online resource.
- Studies in Computational Intelligence, 873 1860-9503 ; .
- Studies in Computational Intelligence, 873 .
An Evolutionary Computing Approach to Solve Object Identification Problem for fall detection in Computer Vision based Video Surveillance Applications -- Texture-dependent Optimal Fractional-order Framework for Image Quality Enhancement through Memetic Inclusions in Cuckoo Search and Sine-Cosine Algorithms -- Artificial Bee Colony: Theory, Literature Review, and Application in Image Segmentation -- Applications of Memetic Algorithms in Image Processing Using Deep Learning -- Recent Applications of Swarm-based Algorithms to Color Quantization -- Hybrid Biogeography Based Optimization Techniques for Geo-Spatial Feature Extraction: A Brief Survey -- An Efficient Copy-move Forgery Detection Technique using Nature-Inspired Optimization Algorithm -- Design and Implementation of Hybrid Plate Tectonics Neighborhood based ADAM’s Optimization and its application on Crop Recommendation -- An Evolutionary Memetic Weighted Associative Classification Algorithm for Heart Disease Prediction.
This book includes original research findings in the field of memetic algorithms for image processing applications. It gathers contributions on theory, case studies, and design methods pertaining to memetic algorithms for image processing applications ranging from defence, medical image processing, and surveillance, to computer vision, robotics, etc. The content presented here provides new directions for future research from both theoretical and practical viewpoints, and will spur further advances in the field.