Description
Book SynopsisFocusing on how visual information is represented, stored and extracted in the human brain, this book uses cognitive neural modeling in order to show how visual information is represented and memorized in the brain.
Breaking through traditional visual information processing methods, the author combines our understanding of perception and memory from the human brain with computer vision technology, and provides a new approach for image recognition and classification. While biological visual cognition models and human brain memory models are established, applications such as pest recognition and carrot detection are also involved in this book.
Given the range of topics covered, this book is a valuable resource for students, researchers and practitioners interested in the rapidly evolving field of neurocomputing, computer vision and machine learning.
Table of Contents1. Introduction 2. Methods of visual perception and memory modeling 3. Bio-inspired model for object recognition based on histogram of oriented gradients 4. Modeling object recognition in visual cortex using multiple firing K-means and non-negative sparse coding 5. Biological modeling of human visual system using GLoP filters and sparse coding on multi-manifolds 6. Increment learning and rapid retrieval of visual information based on pattern association memory 7. Memory modeling based on free energy theory and restricted Boltzmann machine 8. Research on insect pest image detection and recognition based on bio-inspired methods 9. Carrot defect detection and grading based on computer vision and deep learning
