| 书目名称 | Hierarchical Neural Networks for Image Interpretation |
| 编辑 | Sven Behnke |
| 视频video | |
| 概述 | Includes supplementary material: |
| 丛书名称 | Lecture Notes in Computer Science |
| 图书封面 |  |
| 描述 | .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.. |
| 出版日期 | Book 2003 |
| 关键词 | cognition; computer vision; control; learning; neural architectures; neural network; neural network learni |
| 版次 | 1 |
| doi | https://doi.org/10.1007/b11963 |
| isbn_softcover | 978-3-540-40722-5 |
| isbn_ebook | 978-3-540-45169-3Series ISSN 0302-9743 Series E-ISSN 1611-3349 |
| issn_series | 0302-9743 |
| copyright | Springer-Verlag Berlin Heidelberg 2003 |
发表于 2025-3-21 19:50:56
