Recognition of object orientation and shape by a rotation spreading associative neural network
Recognition of object orientation and shape by a rotation spreading associative neural network
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通过旋转扩展关联神经网络识别物体方向和形状
DOI：
10.1109/ijcnn.2001.939084
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发表时间：
2001
期刊：
影响因子：
--
通讯作者：
T. Yoshikawa
中科院分区：
文献类型：
--
作者：
K. Nakamura;Kazuya Arimura;T. Yoshikawa
注意顶叶皮层，我们以前开发了一个旋转扩散联想神经网络（RSAN网络），同时识别的方向和形状的二进制字符和灰度人脸。本文研究了RSAN网络在学习方向和传播方向数目不同以及输入对象在二维空间中移动时的识别性能。基于这些数据，我们开发了一个位置不变的RSAN网络，以允许对象的并行移动。综合考虑识别特征和学习识别时间，当学习方向数等于传播方向数时，RSAN网络的识别性能最佳。然而，RSAN网络对于物体的平行移动是脆弱的;移动最大应该在10个像素内。另一方面，位置不变的RSAN网络实现了位置和形状不变的方向识别（在-60/spl deg/到60/spl deg/）和位置和方向不变的人脸形状识别（在所有角度），同时。
Paying attention to the parietal cortex, we previously developed a rotation spreading associative neural network (RSAN net) that simultaneously recognized the orientation and shape of a binary character and a grayscale human face. The present study investigated the recognition performance of the RSAN net when the numbers of learning directions and spreading directions were changed variously, and when the input object was shifted in two-D space. Based on the data, we then developed a position invariant RSAN net in order to allow for the parallel shifting of an object. The best recognition performance of the RSAN net was obtained when the number of learning directions was equal to the number of spreading directions, taking into account the recognition characteristics and learning and recognition time. However, the RSAN net was fragile to the parallel shift of the object; the shift should be within 10 pixels in maximum. On the other hand, the position invariant RSAN net achieved position and shape invariant orientation recognition (within -60/spl deg/ to 60/spl deg/) and position and orientation invariant shape recognition of human faces (at all angles), simultaneously.
影响因子：
56.9
作者：
ANDERSEN, RA;ESSICK, GK;SIEGEL, RM
通讯作者：
SIEGEL, RM