@inproceedings{eeb5ee69cc5e4eb19c793ed1763530a8,
title = "CSL-YOLO: A Cross-Stage Lightweight Object Detector with Low FLOPs",
abstract = "The development of lightweight object detectors is essential due to the limited computation resources. To reduce the computation cost, how to generate features plays a significant role. This paper proposes a new lightweight convolution method Cross-Stage Lightweight Module (CSL-M). It combines the Inverted Residual Block (IRB) and Cross-Stage Partial (CSP) concept. Experiments conducted at CIFAR-10 show that the proposed CSL-Net based on CSL-M performs better with fewer FLOPs than the other lightweight backbones. Finally, we use CSL-Net as the backbone to construct a lightweight detector CSL-YOLO, achieving better detection performance with only 43% FLOPs and 52% parameters than Tiny-YOLOv4.",
keywords = "lightweight detector, low FLOPs, MS-COCO, YOLO",
author = "Zhang, {Yu Ming} and Lee, {Chun Chieh} and Hsieh, {Jun Wei} and Fan, {Kuo Chin}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Symposium on Circuits and Systems, ISCAS 2022 ; Conference date: 27-05-2022 Through 01-06-2022",
year = "2022",
doi = "10.1109/ISCAS48785.2022.9937880",
language = "???core.languages.en_GB???",
series = "Proceedings - IEEE International Symposium on Circuits and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2730--2734",
booktitle = "IEEE International Symposium on Circuits and Systems, ISCAS 2022",
}