Year: 2015
Journal of Fiber Bioengineering and Informatics, Vol. 8 (2015), Iss. 4 : pp. 791–800
Abstract
In order to enable the industrial robots to recognize the specific targets quickly and accurately on the assembly line, an object recognition method driven by visual selective attention mechanism is proposed. With mass training data and a machine learning model containing a number of hidden layers, deep learning can learn more useful features, and thus ultimately improve the classification or the prediction accuracy. The main idea of this method is as follows: for all part images, the visual attention mechanism is used to choose salient regions in an image, achieving the goal of target segmentation. Then an image recognition method based on deep learning is applied to recognize the chosen salient regions. Experimental results show the effectiveness of the proposed method and the cognitive rationality.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.3993/jfbim00196
Journal of Fiber Bioengineering and Informatics, Vol. 8 (2015), Iss. 4 : pp. 791–800
Published online: 2015-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 10
Keywords: Visual Selective Attention Mechanism
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