A Lightweight Target Detection Network Based on Channel Rearrangement

doi:10.3969/j.issn.1006-2475.2020.02.019

Abstract

Abstract: Tiny YOLO and YOLOv3-tiny are two lightweight target detection algorithms known for their outstanding speed performance. Based on these two network models, combining packet convolution and improved channel rearrangement algorithm and the original loss function， this paper constructs a new faster network model which improves the detection accuracy by improving the loss function of YOLOv3. The PASCAL VOC and COCO datasets were trained and tested respectively. The speed of the network model was faster than 265 pictures per second, and the accuracy was higher than Tiny YOLO and similar to YOLOv3-tiny.

Key words: target detection, network model, loss function, channel shuffle

CLC Number:

TP319.41

XU Han-zhi， AI Zhong-liang， ZHANG Zhi-chao . A Lightweight Target Detection Network Based on Channel Rearrangement [J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2020.02.019.

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