CSL-YOLO: A Cross-Stage Lightweight Object Detector with Low FLOPs

Yu Ming Zhang, Chun Chieh Lee, Jun Wei Hsieh, Kuo Chin Fan

研究成果: 書貢獻/報告類型會議論文篇章同行評審

1 引文 斯高帕斯(Scopus)

摘要

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.

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主出版物標題IEEE International Symposium on Circuits and Systems, ISCAS 2022
發行者Institute of Electrical and Electronics Engineers Inc.
頁面2730-2734
頁數5
ISBN(電子)9781665484855
DOIs
出版狀態已出版 - 2022
事件2022 IEEE International Symposium on Circuits and Systems, ISCAS 2022 - Austin, United States
持續時間: 27 5月 20221 6月 2022

出版系列

名字Proceedings - IEEE International Symposium on Circuits and Systems
2022-May
ISSN(列印)0271-4310

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???event.eventtypes.event.conference???2022 IEEE International Symposium on Circuits and Systems, ISCAS 2022
國家/地區United States
城市Austin
期間27/05/221/06/22

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