图 书 馆
一种用于计算取向优势的生物合理网络A biologically plausible network for the computation of orientation dominance |
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| 课程网址: | http://videolectures.net/nips2010_muralidharan_bpn/ |
| 主讲教师: | Kritika Muralidharan |
| 开课单位: | 圣地亚哥大学 |
| 开课时间: | 2011-03-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The determination of dominant orientation at a given image location is formulated as a decision-theoretic question. This leads to a novel measure for the dominance of a given orientation $\theta$, which is similar to that used by SIFT. It is then shown that the new measure can be computed with a network that implements the sequence of operations of the standard neurophysiological model of V1. The measure can thus be seen as a biologically plausible version of SIFT, and is denoted as bioSIFT. The network units are shown to exhibit trademark properties of V1 neurons, such as cross-orientation suppression, sparseness and independence. The connection between SIFT and biological vision provides a justification for the success of SIFT-like features and reinforces the importance of contrast normalization in computer vision. We illustrate this by replacing the Gabor units of an HMAX network with the new bioSIFT units. This is shown to lead to significant gains for classification tasks, leading to state-of-the-art performance among biologically inspired network models and performance competitive with the best non-biological object recognition systems. |
| 关 键 词: | 计算机科学; 计算生物学; 生物视觉 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-06：zyk |
| 阅读次数: | 26 |