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Recognition Workpiece Based on BP Neural Network

Authors: Shi-xiang Tian; Sheng-ze Wang;

Recognition Workpiece Based on BP Neural Network

Abstract

This research is an attempt to design an Algorithm to recognize workpiece in order to guide a manipulator approach the workpiece and pick it to feed into a mould mounted on platform of the press. Back propagation algorithm is applied on a supervised classification of workpiece images. Several images of the workpiece are used as training samples and were converted into binary forms and to train the network. To ensure the performance of the system, network parameters such as momentum value, learning rate and number of hidden neuron would be adjusted to get the appropriate setting. It is found that the the proposed algorithm can identify the type of workpiece presented.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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