Abstract
Human activities and other factors lead to a variety of floating objects in rivers, which seriously affect the quality of human life and natural ecological environment. It has become a widely concerned problem for residents and needs to be solved urgently. Relying on manual inspection to find floating objects is extremely low efficiency, urgent need of intelligent technology to detect and warn in time. To solve the problem of river floating object detection, we proposed an improved HRNet method for river floating object detection. Trunk network HRNet was used to replace the original AlexNet trunk network of Faster-RCNN to detect river floating object, which enhanced the feature extraction ability. A backbone combining DenseNet and HRNet is proposed to optimize the ability to extract details and improve the detection accuracy.
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