Object Detection Method of Power Equipment Based on Mask R-CNN
DOI:
https://doi.org/10.54097/ajst.v1i2.322Keywords:
Power equipment, Object detection, Mask R-CNNAbstract
With the rapid development of deep learning technology and its outstanding performance in the field of image, more and more researchers begin to pay attention to the application of deep learning in the field of power industry. After analyzing the structure of Mask R-CNN and considering the particularity of infrared image data set, a new Mask R-CNN model is proposed. Channel attention mechanism is introduced to make the network learn the weight coefficient of each channel, so that the network can filter noise more effectively and extract more information related to the object. Experimental results show that the accuracy of the improved model is better than that of the original model, and the effectiveness of the improved method is verified.
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References
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