Biologically Rationalized Computing Techniques For Image Processing Applications

Chapter 1 Artificial Bee Colony Algorithm for Classification of Semi-urban LU/LC Features Using High-Resolution Satellite Data

Chapter 2 Saliency-Based Image Compression Using Walsh–Hadamard Transform (WHT)

Chapter 3 Object Trajectory Prediction with Scarce Environment Information

Chapter 4 A Twofold Subspace Learning-Based Feature Fusion Strategy for Classification of EMG and EMG Spectrogram Images

Chapter 5 Automatic Detection of Brain Strokes in CT Images Using Soft Computing Techniques

Chapter 6 Survey on the Classification of Intelligence-Based Biometric Techniques

Chapter 7 Spatial and Spectral Quality Assessment of Fused Hyperspectral and Multispectral Data

Chapter 8 Deep Learning Techniques for Breast Cancer Detection Using Medical Image Analysis

Chapter 9 A Tour Toward the Development of Various Techniques for Paralysis Detection Using Image Processing

Chapter 11 Review on Image Enhancement Techniques Using Biologically Inspired Artificial Bee Colony Algorithms and Its Variants

Chapter 12 Certain Applications and Case Studies of Evolutionary Computing Techniques for Image Processing

Chapter 13 Histopathological Image Analysis for the Grade Identification of Tumor

Chapter 14 Super-Resolution via Particle Swarm Optimization Variants