{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T20:35:59Z","timestamp":1783024559896,"version":"3.54.6"},"reference-count":38,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T00:00:00Z","timestamp":1662595200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key Research and Development Projects of Hainan Province","award":["ZDYF2022GXJS001"],"award-info":[{"award-number":["ZDYF2022GXJS001"]}]},{"name":"Key Research and Development Projects of Hainan Province","award":["ZR201910300033"],"award-info":[{"award-number":["ZR201910300033"]}]},{"name":"Key Research and Development Projects of Hainan Province","award":["61971253"],"award-info":[{"award-number":["61971253"]}]},{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZDYF2022GXJS001"],"award-info":[{"award-number":["ZDYF2022GXJS001"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZR201910300033"],"award-info":[{"award-number":["ZR201910300033"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["61971253"],"award-info":[{"award-number":["61971253"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["ZDYF2022GXJS001"],"award-info":[{"award-number":["ZDYF2022GXJS001"]}],"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":["ZR201910300033"],"award-info":[{"award-number":["ZR201910300033"]}],"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":["61971253"],"award-info":[{"award-number":["61971253"]}],"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>Intelligent detection of marine organism plays an important part in the marine economy, and it is significant to detect marine organisms quickly and accurately in a complex marine environment for the intelligence of marine equipment. The existing object detection models do not work well underwater. This paper improves the structure of EfficientDet detector and proposes the EfficientDet-Revised (EDR), which is a new marine organism object detection model. Specifically, the MBConvBlock is reconstructed by adding the Channel Shuffle module to enable the exchange of information between the channels of the feature layer. The fully connected layer of the attention module is removed and convolution is used to cut down the amount of network parameters. The Enhanced Feature Extraction module is constructed for multi-scale feature fusion to enhance the feature extraction ability of the network to different objects. The results of experiments demonstrate that the mean average precision (mAP) of the proposed method reaches 91.67% and 92.81% on the URPC dataset and the Kaggle dataset, respectively, which is better than other object detection models. At the same time, the processing speed reaches 37.5 frame per second (FPS) on the URPC dataset, which can meet the real-time requirements. It can provide a useful reference for underwater robots to perform tasks such as intelligent grasping.<\/jats:p>","DOI":"10.3390\/rs14184487","type":"journal-article","created":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T20:50:27Z","timestamp":1662670227000},"page":"4487","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":68,"title":["Underwater Object Detection Based on Improved EfficientDet"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7523-7411","authenticated-orcid":false,"given":"Jiaqi","family":"Jia","sequence":"first","affiliation":[{"name":"College of Electronic Engineering, Ocean University of China, Qingdao 266100, China"},{"name":"Sanya Oceanography Institution, Ocean University of China, Sanya 572024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min","family":"Fu","sequence":"additional","affiliation":[{"name":"College of Electronic Engineering, Ocean University of China, Qingdao 266100, China"},{"name":"Sanya Oceanography Institution, Ocean University of China, Sanya 572024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuefeng","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266061, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bing","family":"Zheng","sequence":"additional","affiliation":[{"name":"College of Electronic Engineering, Ocean University of China, Qingdao 266100, China"},{"name":"Sanya Oceanography Institution, Ocean University of China, Sanya 572024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Fu, H., Song, G., and Wang, Y. 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