Deformable convolutional neural network-based infrared image object identification method
A convolutional neural network and infrared image technology, applied in the field of infrared image object recognition based on deformable convolutional neural network, to achieve the effect of improving performance and recognition performance
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[0035] A method of infrared image object recognition based on deformable convolutional neural network, such as figure 1 shown, including the following steps:
[0036] S1: Collect database samples and set training set and test set. The training set uses COCO. The images in this dataset include 91 types of targets, 328,000 images and 2,500,000 labels. And set the coding of each category in the classifier, for example, the three types of objects car, monkey, and potted plants are coded as 100, 010 and 001 respectively. The test set uses infrared images of substation equipment.
[0037] S2: Build a convolutional neural network architecture, and set the depth and width architecture of the convolutional neural network by overlapping several convolutional layers and pooling layers;
[0038] S3: Use a deformable convolution kernel for sampling in the convolutional layer, learn the offset offset by adding an additional convolutional layer, share the input feature map, and then use th...
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