Cognitive and Neural Modelling for Visual Information Representation and Memorization

1. Auflage 2024
ISBN: 978-1-032-25119-6
Verlag: CRC Press

Buch, Englisch, 259 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 382 g

Focusing 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.

Zielgruppe

Postgraduate and Professional

Autoren/Hrsg.

Deng, Limiao

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Spiele-Programmierung, Rendering, Animation
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung

Inhaltsverzeichnis

1. 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

Über Autor(innen)

Limiao Deng is currently working as an associate professor in Qingdao Agriculture University, China. She received the Ph.D. degree in Control Theory and Control Engineering from China University of Petroleum in 2018. Her areas of research include computer vision, machine learning and pattern recognition. She is also a regular reviewer of journals of repute namely IEEE, Springer, Elsevier, etc.