Part Recognition Method Based on Visual Selective Attention Mechanism and Deep Learning (Journal of Fiber Bioengineering and Informatics, 2015)
In order to enable the industrial robots to recognize the specific targets quickly and accurately on the\rassembly line, an object recognition method driven by visual selective attention mechanism is proposed.\rWith mass training data and a machine learning model containing a number of hidden layers, deep\rlearning can learn more useful features, and thus ultimately improve the classification or the prediction\raccuracy. The main idea of this method is as follows: for all part images, the visual attention mechanism\ris used to choose salient regions in an image, achieving the goal of target segmentation. Then an\rimage recognition method based on deep learning is applied to recognize the chosen salient regions.\rExperimental results show the effectiveness of the proposed method and the cognitive rationality.
Keywords: Visual Selective Attention Mechanism; Part Recognition; Deep Learning; Feature Learning