{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T07:43:15Z","timestamp":1765438995338,"version":"build-2065373602"},"reference-count":42,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2024,10,14]],"date-time":"2024-10-14T00:00:00Z","timestamp":1728864000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2022YFC2808003","23-2-1-100-zyyd-jch"],"award-info":[{"award-number":["2022YFC2808003","23-2-1-100-zyyd-jch"]}]},{"name":"Natural Science Foundation of Qingdao Municipality","award":["2022YFC2808003","23-2-1-100-zyyd-jch"],"award-info":[{"award-number":["2022YFC2808003","23-2-1-100-zyyd-jch"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Marine mammal acoustic signal recognition is a key technology for species conservation and ecological environment monitoring. Aiming at the complex and changing marine environment, and because the traditional recognition method based on a single feature input has the problems of poor environmental adaptability and low recognition accuracy, this paper proposes a dual-feature fusion learning method. First, dual-domain feature extraction is performed on marine mammal acoustic signals to overcome the limitations of single feature input methods by interacting feature information between the time-frequency domain and the Delay-Doppler domain. Second, this paper constructs a dual-feature fusion learning target recognition model, which improves the generalization ability and robustness of mammal acoustic signal recognition in complex marine environments. Finally, the feasibility and effectiveness of the dual-feature fusion learning target recognition model are verified in this study by using the acoustic datasets of three marine mammals, namely, the Fraser\u2019s Dolphin, the Spinner Dolphin, and the Long-Finned Pilot Whale. The dual-feature fusion learning target recognition model improved the accuracy of the training set by 3% to 6% and 20% to 23%, and the accuracy of the test set by 1% to 3% and 25% to 38%, respectively, compared to the model that used the time-frequency domain features and the Delay-Doppler domain features alone for recognition.<\/jats:p>","DOI":"10.3390\/rs16203823","type":"journal-article","created":{"date-parts":[[2024,10,14]],"date-time":"2024-10-14T12:44:31Z","timestamp":1728909871000},"page":"3823","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Dual-Feature Fusion Learning: An Acoustic Signal Recognition Method for Marine Mammals"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6251-4435","authenticated-orcid":false,"given":"Zhichao","family":"L\u00fc","sequence":"first","affiliation":[{"name":"College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China"}]},{"given":"Yaqian","family":"Shi","sequence":"additional","affiliation":[{"name":"College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China"}]},{"given":"Liangang","family":"L\u00fc","sequence":"additional","affiliation":[{"name":"First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China"}]},{"given":"Dongyue","family":"Han","sequence":"additional","affiliation":[{"name":"College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China"}]},{"given":"Zhengkai","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China"}]},{"given":"Fei","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1525\/9780520321373-029","article-title":"Sonic-ultrasonic emissions of the bottlenose dolphin","volume":"165","author":"Lilly","year":"1966","journal-title":"Whales Dolphins Porpoises"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1633","DOI":"10.1111\/brv.12969","article-title":"Ecological inferences about marine mammals from passive acoustic data","volume":"98","author":"Fleishman","year":"2023","journal-title":"Biol. 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