Wenshun Sheng*, Xiongfeng Yu, Jiayan Lin, Xin Chen
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1549-1569, 2023, DOI:10.32604/csse.2023.039410
Abstract Small targets and occluded targets will inevitably appear in the image during the shooting process due to the influence of angle, distance, complex scene, illumination intensity, and other factors. These targets have few effective pixels, few features, and no apparent features, which makes extracting their efficient features difficult and easily leads to false detection, missed detection, and repeated detection, affecting the performance of target detection models. An improved faster region convolutional neural network (RCNN) algorithm (CF-RCNN) integrating convolutional block attention module (CBAM) and feature pyramid networks (FPN) is proposed to improve the detection and recognition accuracy of small-size objects, occluded… More >
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