Hierarchical Neural Networks for Image Interpretation

Download or read book Hierarchical Neural Networks for Image Interpretation written by Sven Behnke and published by Springer. This book was released on 2003-11-18 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human performance in visual perception by far exceeds the performance of contemporary computer vision systems. While humans are able to perceive their environment almost instantly and reliably under a wide range of conditions, computer vision systems work well only under controlled conditions in limited domains. This book sets out to reproduce the robustness and speed of human perception by proposing a hierarchical neural network architecture for iterative image interpretation. The proposed architecture can be trained using unsupervised and supervised learning techniques. Applications of the proposed architecture are illustrated using small networks. Furthermore, several larger networks were trained to perform various nontrivial computer vision tasks.