Receptive field enhancement and attention feature fusion network for underwater object detection
Huipu Xu,
Zegang He,
Shuo Chen
Abstract:Underwater environments have characteristics such as unclear imaging and complex backgrounds that lead to poor performance when applying mainstream object detection models directly. To improve the accuracy of underwater object detection, we propose an object detection model, RF-YOLO, which uses a receptive field enhancement (RFE) module in the backbone network to finish RFE and extract more effective features. We design the free-channel iterative attention feature fusion module to reconstruct the neck network … Show more
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