Pingping Yu1, Hongda Wang1, Xiaodong Zhao1,*, Guangchen Ruan2
CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4261-4276, 2022, DOI:10.32604/cmc.2022.029239
Abstract Aiming at the problems of low target image resolution, insufficient target feature extraction, low detection accuracy and poor real time in remote engineering vehicle detection, an improved CenterNet target detection model is proposed in this paper. Firstly, EfficientNet-B0 with Efficient Channel Attention (ECA) module is used as the basic network, which increases the quality and speed of feature extraction and reduces the number of model parameters. Then, the proposed Adaptive Fusion Bidirectional Feature Pyramid Network (AF-BiFPN) module is applied to fuse the features of different feature layers. Furthermore, the feature information of engineering vehicle targets is added by making full… More >
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