{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T23:02:06Z","timestamp":1775862126673,"version":"3.50.1"},"reference-count":52,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2022,10,23]],"date-time":"2022-10-23T00:00:00Z","timestamp":1666483200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA19010102"],"award-info":[{"award-number":["XDA19010102"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["61975222"],"award-info":[{"award-number":["61975222"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["XDA19010102"],"award-info":[{"award-number":["XDA19010102"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61975222"],"award-info":[{"award-number":["61975222"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The development of infrared remote sensing technology improves the ability of night target observation, and thermal imaging systems (TIS) play a key role in the military field. Ship detection using thermal infrared (TI) remote sensing images (RSIs) has aroused great interest for fishery supervision, port management, and maritime safety. However, due to the high secrecy level of infrared data, thermal infrared ship datasets are lacking. In this paper, a new three-bands thermal infrared ship dataset (TISD) is proposed to evaluate all-day ship target detection algorithms. All images are from SDGSAT-1 satellite TIS three bands RSIs of the real world. Based on the TISD, we use the state-of-the-art algorithm as a baseline to do the following. (1) Common ship detection methods and existing ship datasets from synthetic aperture radar, visible, and infrared images are elementarily summarized. (2) The proposed standard deviation of single band, correlation coefficient of combined bands, and optimum index factor features of three-bands datasets are analyzed, respectively. Combined with the above theoretical analysis, the influence of the bands\u2019 information input on the detection accuracy of a neural network model is explored. (3) We construct a lightweight network based on Yolov5 to reduce the number of floating-point operations, which is beneficial to reduce the inference time. (4) By utilizing up-sampling and registration pre-processing methods, TI images are fused with glimmer RSIs to verify the detection accuracy at night. In practice, the proposed datasets are expected to promote the research and application of all-day ship detection.<\/jats:p>","DOI":"10.3390\/rs14215297","type":"journal-article","created":{"date-parts":[[2022,10,24]],"date-time":"2022-10-24T10:09:23Z","timestamp":1666606163000},"page":"5297","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["TISD: A Three Bands Thermal Infrared Dataset for All Day Ship Detection in Spaceborne Imagery"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7840-1600","authenticated-orcid":false,"given":"Liyuan","family":"Li","sequence":"first","affiliation":[{"name":"Key Laboratory of Intelligent Infrared Perception, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, 500 Yu Tian Road, Shanghai 200083, China"},{"name":"International Research Center of Big Data for Sustainable Development Goals (CBAS), Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Jianing","family":"Yu","sequence":"additional","affiliation":[{"name":"International Research Center of Big Data for Sustainable Development Goals (CBAS), Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2244-8327","authenticated-orcid":false,"given":"Fansheng","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Infrared Perception, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, 500 Yu Tian Road, Shanghai 200083, China"},{"name":"International Research Center of Big Data for Sustainable Development Goals (CBAS), Beijing 100094, China"},{"name":"Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zhao, D., Zhu, C., Qi, J., Qi, X., Su, Z., and Shi, Z. 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