{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T11:40:03Z","timestamp":1755862803117,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":26,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,2,2]],"date-time":"2024-02-02T00:00:00Z","timestamp":1706832000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"the National Natural Science Foundation of China","award":["61973083"],"award-info":[{"award-number":["61973083"]}]},{"name":"Shenzhen Science and Technology Program","award":["JCYJ20210324121213036"],"award-info":[{"award-number":["JCYJ20210324121213036"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,2,2]]},"DOI":"10.1145\/3651671.3651761","type":"proceedings-article","created":{"date-parts":[[2024,6,7]],"date-time":"2024-06-07T18:55:50Z","timestamp":1717786550000},"page":"271-279","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Visual-Based Detection Method for Oil Leakage in Antarctic Power-Generation Cabin"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-2548-3569","authenticated-orcid":false,"given":"Xiao","family":"Ge","sequence":"first","affiliation":[{"name":"School of Automation, Southeast University, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-8240-4655","authenticated-orcid":false,"given":"Tao","family":"Wang","sequence":"additional","affiliation":[{"name":"Polar Research Institute of China, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0914-7685","authenticated-orcid":false,"given":"Kanjian","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Automation, Southeast University, China"}]}],"member":"320","published-online":{"date-parts":[[2024,6,7]]},"reference":[{"issue":"2","key":"e_1_3_2_1_1_1","first-page":"98","article-title":"Design and Test of Unattended Power Supply Test Device for Taishan Station","volume":"41","author":"Ge J.","year":"2020","unstructured":"Ge, J. & Fang, S. X. 2020 Design and Test of Unattended Power Supply Test Device for Taishan Station. Process Automation Instrumentation, 41(2), 98-101.","journal-title":"Process Automation Instrumentation"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultras.2004.02.013"},{"key":"e_1_3_2_1_3_1","volume-title":"Flow field and noise characteristics of manifold in natural gas transportation station. Oil & Gas Science and Technology\u2013Revue d'IFP Energies nouvelles, 74, 70","author":"Su Z.","year":"2019","unstructured":"Su, Z., Liu, E., Xu, Y., Xie, P., Shang, C., & Zhu, Q. (2019). Flow field and noise characteristics of manifold in natural gas transportation station. Oil & Gas Science and Technology\u2013Revue d'IFP Energies nouvelles, 74, 70."},{"key":"e_1_3_2_1_4_1","first-page":"178","volume-title":"Fertigung, Pr\u00fcfung, Eigenschaften und Anwendungen technischer Werkstoffe, 40(3)","author":"Kuzmani\u0107 I.","year":"2009","unstructured":"Kuzmani\u0107, I., \u0160oda, J., Antoni\u0107, R., Vujovi\u0107, I., & Bero\u0161, S. (2009). Monitoring of oil leakage from a ship propulsion system using IR camera and wavelet analysis for prevention of health and ecology risks and engine faults. Materialwissenschaft und Werkstofftechnik: Entwicklung, Fertigung, Pr\u00fcfung, Eigenschaften und Anwendungen technischer Werkstoffe, 40(3), 178-186."},{"key":"e_1_3_2_1_5_1","volume-title":"Small Amounts of Transformer Oil Leakage Fluorescence Detection Using Image Processing. In 2022 IEEE 5th International Electrical and Energy Conference (CIEEC) (pp. 86-91)","author":"Li X. X.","year":"2022","unstructured":"Li, X. X., Zhang, W. H., Liu, X. J., Yang, X. M., & Ma, X. M. (2022). Small Amounts of Transformer Oil Leakage Fluorescence Detection Using Image Processing. In 2022 IEEE 5th International Electrical and Energy Conference (CIEEC) (pp. 86-91). IEEE."},{"issue":"06","key":"e_1_3_2_1_6_1","first-page":"55","article-title":"Detection of Water and Oil Leakage in Production Area of Power Plant Based on lmproved YOLOv3 Model","volume":"34","author":"Gong Y.","year":"2021","unstructured":"Gong Y., Lu, C. D., FU Y., Q., Yi T., T., & Zhou J., H. (2021) Detection of Water and Oil Leakage in Production Area of Power Plant Based on lmproved YOLOv3 Model. Guangdong Electric Power, 34(06), 55-64.","journal-title":"Guangdong Electric Power"},{"key":"e_1_3_2_1_7_1","volume-title":"International Conference on Internet of Things (pp. 90-101)","author":"Gao M.","year":"2021","unstructured":"Gao, M., Zhang, C., Xu, C., Gao, Q., Gao, J., Yan, J., ... & Tu, H. (2021). Electric Transformer Oil Leakage Visual Detection as Service Based on LSTM and Genetic Algorithm. In International Conference on Internet of Things (pp. 90-101). Cham: Springer International Publishing."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.3390\/en15124238"},{"key":"e_1_3_2_1_9_1","volume-title":"MBLLEN: Low-Light Image\/Video Enhancement Using CNNs. In 2018 British Machine Vision Conference (BMVC) (pp. 220-232)","author":"Lv F.","year":"2018","unstructured":"Lv, F., Lu, F., Wu, J., & Lim, C. (2018). MBLLEN: Low-Light Image\/Video Enhancement Using CNNs. In 2018 British Machine Vision Conference (BMVC) (pp. 220-232)."},{"key":"e_1_3_2_1_10_1","volume-title":"Image quality assessment: from error visibility to structural similarity","author":"Wang Z.","year":"2004","unstructured":"Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004). Image quality assessment: from error visibility to structural similarity. IEEE transactions on image processing, 13(4), 600-612."},{"key":"e_1_3_2_1_11_1","volume-title":"Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556","author":"Simonyan K.","year":"2014","unstructured":"Simonyan, K., & Zisserman, A. (2014). Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556."},{"key":"e_1_3_2_1_12_1","first-page":"123","volume-title":"YIQ, LAB, HSV, and opponent color models. ACM Transactions on Graphics (tog), 6(2)","author":"Schwarz M. W.","year":"1987","unstructured":"Schwarz, M. W., Cowan, W. B., & Beatty, J. C. (1987). An experimental comparison of RGB, YIQ, LAB, HSV, and opponent color models. ACM Transactions on Graphics (tog), 6(2), 123-158."},{"issue":"02","key":"e_1_3_2_1_13_1","first-page":"224","article-title":"A Method for Measuring the Height and Area Based on Distance Estimation of Monocular Vision","volume":"16","author":"Qu S. S.","year":"2016","unstructured":"Qu, S. S., Chen, X., Wu, X. H., Yang, Q. 2016 A Method for Measuring the Height and Area Based on Distance Estimation of Monocular Vision. Science Technology and Engineering, 16(02), 224-228.","journal-title":"Science Technology and Engineering"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/RASSE53195.2021.9686859"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/IPEC51340.2021.9421144"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2794218"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00255"},{"key":"e_1_3_2_1_18_1","volume-title":"Deep retinex decomposition for low-light enhancement. arXiv preprint arXiv:1808.04560","author":"Wei C.","year":"2018","unstructured":"Wei, C., Wang, W., Yang, W., & Liu, J. (2018). Deep retinex decomposition for low-light enhancement. arXiv preprint arXiv:1808.04560."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-020-01407-x"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00555"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00581"},{"key":"e_1_3_2_1_22_1","volume-title":"Making a \u201ccompletely blind","author":"Mittal A.","year":"2012","unstructured":"Mittal, A., Soundararajan, R., & Bovik, A. C. (2012). Making a \u201ccompletely blind\u201d image quality analyzer. IEEE Signal processing letters, 20(3), 209-212."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2013.2261309"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2012.2214050"},{"key":"e_1_3_2_1_25_1","volume-title":"Statistical aspects of Wasserstein distances. Annual review of statistics and its application, 6, 405-431","author":"Panaretos V. M.","year":"2019","unstructured":"Panaretos, V. M., & Zemel, Y. (2019). Statistical aspects of Wasserstein distances. Annual review of statistics and its application, 6, 405-431."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6999"}],"event":{"name":"ICMLC 2024: 2024 16th International Conference on Machine Learning and Computing","acronym":"ICMLC 2024","location":"Shenzhen China"},"container-title":["Proceedings of the 2024 16th International Conference on Machine Learning and Computing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3651671.3651761","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3651671.3651761","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T11:22:14Z","timestamp":1755861734000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3651671.3651761"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2,2]]},"references-count":26,"alternative-id":["10.1145\/3651671.3651761","10.1145\/3651671"],"URL":"https:\/\/doi.org\/10.1145\/3651671.3651761","relation":{},"subject":[],"published":{"date-parts":[[2024,2,2]]},"assertion":[{"value":"2024-06-07","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}