Image recognition technology based on neural network in robot vision system
by Yinggang He
International Journal of Grid and Utility Computing (IJGUC), Vol. 12, No. 4, 2021

Abstract: This research uses CamVid training decoder to train the model, then fine tune the parameters on the collected data, label the manually collected data with LabetMe annotation tool, and cross verify the image and scene with neural network algorithm and image recognition principle technology. After five training cycles, the neural network in this study can achieve more than 90% recognition accuracy, and achieve convergence after storing about 10 cycles. Finally, the recognition accuracy in the test data set can reach more than 95%. In the range of robot vision recognition, the maximum measurement deviation is only 2.54 cm and the error is less than 2%. It can be concluded that the method used in this study has fast convergence speed, high recognition accuracy, small error, and good practicability and effectiveness.

Online publication date: Thu, 09-Dec-2021

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