fig1

Figure 1. Schematic diagram of the neural network applied. The network was modified based on the YOLOv3 model, and the image was scaled and adjusted to 960 × 540 and input in the form of RGB three channels. CBL was the image feature extraction module, using max-pooling for downsampling and deconvolution to upsample the image after 4 times of downsampling. The feature maps corresponding to the layers were concatenated with the upsampled feature maps (Concat). Finally, the feature maps obtained after 32 times sampling, 16 times sampling, and 8 times sampling were input into the YOLO-Network as the anchor to generate anchor matching and generate the final prediction frame. This figure was created using DrawIO. CBL: Convolution+Batch normalization+Leaky-Relu; Conv: Convolution; Deconv: Deconvolution; RGB: red-green-blue.