Jun Wang1, Tingjuan Zhang2,*, Yong Cheng3, Prof Mingshun Jiang4
Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 927-940, 2022, DOI:10.32604/iasc.2022.026847
Abstract To obtain the most intuitive pedestrian target detection results and avoid the impact of motion pose uncertainty on real-time detection, a pedestrian target detection system based on a convolutional neural network was designed. Dynamic Selection of Optional Feature (DSOF) module and a center branch were proposed in this paper, and the target was detected by an anchor-free method. Although almost all the most advanced target detectors use pre-defined anchor boxes to run through the possible positions, scales, and aspect ratios of search targets, their effectualness, and generalization ability are also limited by the anchor boxes. Most anchor-based detectors use heuristically… More >
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