{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:40:29Z","timestamp":1760150429551,"version":"build-2065373602"},"reference-count":55,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2023,11,29]],"date-time":"2023-11-29T00:00:00Z","timestamp":1701216000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFC3103101","GML2021GD0809","42206187","2023ZDZX4009"],"award-info":[{"award-number":["2022YFC3103101","GML2021GD0809","42206187","2023ZDZX4009"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory","award":["2022YFC3103101","GML2021GD0809","42206187","2023ZDZX4009"],"award-info":[{"award-number":["2022YFC3103101","GML2021GD0809","42206187","2023ZDZX4009"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2022YFC3103101","GML2021GD0809","42206187","2023ZDZX4009"],"award-info":[{"award-number":["2022YFC3103101","GML2021GD0809","42206187","2023ZDZX4009"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key projects of the Guangdong Education Department","award":["2022YFC3103101","GML2021GD0809","42206187","2023ZDZX4009"],"award-info":[{"award-number":["2022YFC3103101","GML2021GD0809","42206187","2023ZDZX4009"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Arctic sea ice plays an important role in Arctic-related research. Therefore, how to identify Arctic sea ice from remote sensing images with high quality in an unavoidable noise environment is an urgent challenge to be solved. In this paper, a constrained energy minimization (CEM) method is applied for Arctic sea ice identification, which only requires the target spectrum. Moreover, an error-accumulation enhanced neural dynamics (EAEND) model with strong noise immunity and high computing accuracy is proposed to aid with the CEM method for Arctic sea ice identification. With the theoretical analysis, the proposed EAEND model possesses a small steady-state error in noisy environments. Finally, compared with other existing models, the proposed EAEND model can not only complete sea ice identification in excellent fashion, but also has the advantages of high efficiency and noise immunity.<\/jats:p>","DOI":"10.3390\/rs15235555","type":"journal-article","created":{"date-parts":[[2023,11,29]],"date-time":"2023-11-29T12:01:00Z","timestamp":1701259260000},"page":"5555","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Ice Identification with Error-Accumulation Enhanced Neural Dynamics in Optical Remote Sensing Images"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1473-0517","authenticated-orcid":false,"given":"Yizhen","family":"Xiong","sequence":"first","affiliation":[{"name":"School of Electronics and Information Engineering, Guangdong Ocean University, Zhanjiang 524025, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7747-3082","authenticated-orcid":false,"given":"Difeng","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0426-4356","authenticated-orcid":false,"given":"Dongyang","family":"Fu","sequence":"additional","affiliation":[{"name":"School of Electronics and Information Engineering, Guangdong Ocean University, Zhanjiang 524025, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0896-5192","authenticated-orcid":false,"given":"Haoen","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430070, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1080\/19407963.2017.1324861","article-title":"Geopolitics and Tourism in the Arctic: The Case of the National Park \u2018Russian Arctic\u2019","volume":"10","author":"Zelenskaya","year":"2018","journal-title":"J. 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