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Research on Target Detection and Recognition Algorithm Based on Deep Learning

Hui Wang, Chaoda Liu, Lijun Yu, Jingyuan Zhao

Year
2019
Citations
8

Abstract

With the rapid development of robotics, people have higher requirements for detection and recognition of targets. The traditional target recognition algorithm can identify the type of the target, but can not identify the position information of the target, and the recognition rate of the traditional target recognition algorithm is low when the same target appears in the image. To this end, this paper proposes a target detection and recognition algorithm based on deep learning technology using convolutional neural network and region segmentation. The algorithm uses the region proposal to segment the image in the recognition process, which can recognize the type of target and precisely calibrate the position of the target in the image. The simulation results show that the algorithm has a high recognition rate and is sensitive to small target recognition.

Keywords

Artificial intelligenceComputer sciencePattern recognition (psychology)Convolutional neural networkPosition (finance)SegmentationAutomatic target recognitionDeep learningImage segmentationArtificial neural network

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