{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T05:43:38Z","timestamp":1757310218543,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":19,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T00:00:00Z","timestamp":1659571200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,8,4]]},"DOI":"10.1145\/3556384.3556420","type":"proceedings-article","created":{"date-parts":[[2022,10,29]],"date-time":"2022-10-29T10:51:35Z","timestamp":1667040695000},"page":"234-241","source":"Crossref","is-referenced-by-count":2,"title":["YOLOX-based ship target detection for Shore-based monitoring"],"prefix":"10.1145","author":[{"given":"Jixiang","family":"Liu","sequence":"first","affiliation":[{"name":"Navigation College, Dalian Maritime University, China"}]},{"given":"Wenli","family":"Sun","sequence":"additional","affiliation":[{"name":"Navigation College, Dalian Maritime University, China"}]}],"member":"320","published-online":{"date-parts":[[2022,10,29]]},"reference":[{"issue":"02","key":"e_1_3_2_1_1_1","first-page":"55","article-title":"Application of intelligent video surveillance system in offshore oil field","volume":"48","author":"Kun Wang","year":"2021","unstructured":"Wang Kun , Qu Zhi , Shi Xiao Dong , and Chen Qi Shuai . 2021 . Application of intelligent video surveillance system in offshore oil field . Tianjin Science and Technology. 48 ( 02 ), 55 - 56 +61. https:\/\/doi.org\/10.14099\/j.cnki.tjkj.2021.02.017 10.14099\/j.cnki.tjkj.2021.02.017 Wang Kun, Qu Zhi, Shi Xiao Dong, and Chen Qi Shuai. 2021. Application of intelligent video surveillance system in offshore oil field. Tianjin Science and Technology. 48(02), 55-56+61. https:\/\/doi.org\/10.14099\/j.cnki.tjkj.2021.02.017","journal-title":"Tianjin Science and Technology."},{"key":"#cr-split#-e_1_3_2_1_2_1.1","doi-asserted-by":"crossref","unstructured":"Ryan Wen Liu Weiqiao Yuan Xianqing Chen and Yuxu. 2021. An enhanced CNN-enabled learning method for promoting ship detection in maritime surveillance system. ScienceDirect. Ocean Engineering. 235. https:\/\/doi.org\/10.1016\/j.oceaneng.2021.109435 10.1016\/j.oceaneng.2021.109435","DOI":"10.1016\/j.oceaneng.2021.109435"},{"key":"#cr-split#-e_1_3_2_1_2_1.2","doi-asserted-by":"crossref","unstructured":"Ryan Wen Liu Weiqiao Yuan Xianqing Chen and Yuxu. 2021. An enhanced CNN-enabled learning method for promoting ship detection in maritime surveillance system. ScienceDirect. Ocean Engineering. 235. https:\/\/doi.org\/10.1016\/j.oceaneng.2021.109435","DOI":"10.1016\/j.oceaneng.2021.109435"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2865686"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.91"},{"key":"e_1_3_2_1_5_1","volume-title":"YOLOX: Exceeding YOLO Series in","author":"Zheng Ge","year":"2021","unstructured":"Ge Zheng , Liu Songtao , Wang Feng , and Li Zeming . 2021 . YOLOX: Exceeding YOLO Series in 2021. http:\/\/dx.doi.org\/10.48550\/arXiv.2107.08430 10.48550\/arXiv.2107.08430 Ge Zheng, Liu Songtao, Wang Feng, and Li Zeming. 2021. YOLOX: Exceeding YOLO Series in 2021. http:\/\/dx.doi.org\/10.48550\/arXiv.2107.08430"},{"key":"#cr-split#-e_1_3_2_1_6_1.1","unstructured":"Bochkovskiy Alexey Wang Chienyao and Liao Hongyuan. 2020. YOLOv4: Optimal Speed and Accuracy of Object Detection. http:\/\/dx.doi.org\/10.48550\/arXiv.2004.10934 10.48550\/arXiv.2004.10934"},{"key":"#cr-split#-e_1_3_2_1_6_1.2","unstructured":"Bochkovskiy Alexey Wang Chienyao and Liao Hongyuan. 2020. YOLOv4: Optimal Speed and Accuracy of Object Detection. http:\/\/dx.doi.org\/10.48550\/arXiv.2004.10934"},{"key":"e_1_3_2_1_7_1","unstructured":"YOLO-V5. August 13 2020 from https:\/\/github.com\/ultralytics\/yolov5  YOLO-V5. August 13 2020 from https:\/\/github.com\/ultralytics\/yolov5"},{"key":"#cr-split#-e_1_3_2_1_8_1.1","unstructured":"Joseph Redmon and Ali Farhadi. 2018. YOLOv3: An Incremental Improvement. http:\/\/dx.doi.org\/10.48550\/arXiv.1804.02767 10.48550\/arXiv.1804.02767"},{"key":"#cr-split#-e_1_3_2_1_8_1.2","unstructured":"Joseph Redmon and Ali Farhadi. 2018. YOLOv3: An Incremental Improvement. http:\/\/dx.doi.org\/10.48550\/arXiv.1804.02767"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2021.3137817","article-title":"AFSar: An Anchor-Free SAR Target Detection Algorithm Based on Multiscale Enhancement Representation Learning","volume":"60","author":"Huiyao Wan","year":"2022","unstructured":"Wan Huiyao . Chen Jie . Huang Zhixiang . Xia RunFan . Wu BoCai . 2022 . AFSar: An Anchor-Free SAR Target Detection Algorithm Based on Multiscale Enhancement Representation Learning . IEEE Transactions on Geoscience and Remote Sensing , vol. 60 , pp. 1 - 14 . http:\/\/dx.doi.org\/10.1109\/TGRS.2021.3137817 10.1109\/TGRS.2021.3137817 Wan Huiyao. Chen Jie. Huang Zhixiang. Xia RunFan. Wu BoCai. 2022. AFSar: An Anchor-Free SAR Target Detection Algorithm Based on Multiscale Enhancement Representation Learning. IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-14. http:\/\/dx.doi.org\/10.1109\/TGRS.2021.3137817","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"e_1_3_2_1_10_1","first-page":"13","volume-title":"Proceedings of IEEE 3rd International Conference on Power Data Science (ICPDS).IEEE","author":"Liu Bingqian","year":"2021","unstructured":"Bingqian Liu . Jianye Huang . Shuang Lin . Yan Yang and Yincheng Qi. 2021. Improved YOLOX-S Abnormal Condition Detection for Power Transmission Line Corridors . In Proceedings of IEEE 3rd International Conference on Power Data Science (ICPDS).IEEE , Harbin , pp. 13 - 16 . http:\/\/dx.doi.org\/10.1109\/ICPDS54746. 2021 .9690074 10.1109\/ICPDS54746.2021.9690074 Bingqian Liu. Jianye Huang. Shuang Lin. Yan Yang and Yincheng Qi. 2021. Improved YOLOX-S Abnormal Condition Detection for Power Transmission Line Corridors. In Proceedings of IEEE 3rd International Conference on Power Data Science (ICPDS).IEEE, Harbin, pp. 13-16. http:\/\/dx.doi.org\/10.1109\/ICPDS54746.2021.9690074"},{"key":"e_1_3_2_1_11_1","volume-title":"Jianwen Chen and Wei Wang","author":"Wang Jinhai","year":"2021","unstructured":"Jinhai Wang . Zongyin Zhang . Lufeng Luo . Wenbo Zhu . Jianwen Chen and Wei Wang . 2021 . SwinGD: A Robust Grape Bunch Detection Model Based on Swin Transformer in Complex Vineyard Environment. Horticulturae 2021, 7(11), 492. https:\/\/doi.org\/10.3390\/horticulturae7110492 10.3390\/horticulturae7110492 Jinhai Wang. Zongyin Zhang. Lufeng Luo. Wenbo Zhu. Jianwen Chen and Wei Wang. 2021. SwinGD: A Robust Grape Bunch Detection Model Based on Swin Transformer in Complex Vineyard Environment. Horticulturae 2021, 7(11), 492. https:\/\/doi.org\/10.3390\/horticulturae7110492"},{"issue":"3","key":"e_1_3_2_1_12_1","doi-asserted-by":"crossref","first-page":"781","DOI":"10.1109\/TCSVT.2019.2897980","article-title":"Saliency-aware convolution neural network for ship detection in surveillance video","volume":"30","author":"Zhenfeng Shao","year":"2019","unstructured":"Shao Zhenfeng , Wu Wenjing , Wang Zhongyuan , Du Wang , and Wu Wenjing . 2019 . Saliency-aware convolution neural network for ship detection in surveillance video . IEEE Trans. Circuits Syst. Video Technol. 30 ( 3 ), 781 \u2013 794 . http:\/\/dx.doi.org\/10.1109\/TCSVT.2019.2897980. 10.1109\/TCSVT.2019.2897980 Shao Zhenfeng, Wu Wenjing, Wang Zhongyuan, Du Wang, and Wu Wenjing. 2019. Saliency-aware convolution neural network for ship detection in surveillance video. IEEE Trans. Circuits Syst. Video Technol. 30 (3), 781\u2013794. http:\/\/dx.doi.org\/10.1109\/TCSVT.2019.2897980.","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.3390\/sym13020308"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.3390\/rs13040660"},{"key":"e_1_3_2_1_15_1","volume-title":"Shangmao Ai and Xiaoqiang Sun","author":"Liu Tao","year":"2020","unstructured":"Tao Liu . Bo Pang . Shangmao Ai and Xiaoqiang Sun . 2020 . Study on Visual Detection Algorithm of Sea Surface Targets Based on Improved YOLOv3. Sensors , 20. http:\/\/dx.doi.org\/10.3390\/s20247263 10.3390\/s20247263 Tao Liu. Bo Pang. Shangmao Ai and Xiaoqiang Sun. 2020. Study on Visual Detection Algorithm of Sea Surface Targets Based on Improved YOLOv3. Sensors, 20. http:\/\/dx.doi.org\/10.3390\/s20247263"},{"issue":"10","key":"e_1_3_2_1_16_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2021\/1060182","article-title":"ShipYOLO: An Enhanced Model for Ship Detection","volume":"2021","author":"Han Xu","year":"2021","unstructured":"Xu Han . Lining Zhao . Yue Ning and Jingfeng Hu . 2021 . ShipYOLO: An Enhanced Model for Ship Detection . Journal of Advanced Transportation. 2021 ( 10 ): 1 - 11 . http:\/\/dx.doi.org\/10.1155\/2021\/1060182 10.1155\/2021 Xu Han. Lining Zhao. Yue Ning and Jingfeng Hu.2021. ShipYOLO: An Enhanced Model for Ship Detection. Journal of Advanced Transportation. 2021(10):1-11. http:\/\/dx.doi.org\/10.1155\/2021\/1060182","journal-title":"Journal of Advanced Transportation."}],"event":{"name":"SPML 2022: 2022 5th International Conference on Signal Processing and Machine Learning","acronym":"SPML 2022","location":"Dalian China"},"container-title":["2022 5th International Conference on Signal Processing and Machine Learning"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3556384.3556420","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3556384.3556420","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:00:32Z","timestamp":1750186832000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3556384.3556420"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,4]]},"references-count":19,"alternative-id":["10.1145\/3556384.3556420","10.1145\/3556384"],"URL":"https:\/\/doi.org\/10.1145\/3556384.3556420","relation":{},"subject":[],"published":{"date-parts":[[2022,8,4]]}}}