{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T21:53:09Z","timestamp":1791582789489,"version":"4.3.4"},"reference-count":19,"publisher":"Wiley","license":[{"start":{"date-parts":[[2020,5,22]],"date-time":"2020-05-22T00:00:00Z","timestamp":1590105600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["HEUCF180105"],"award-info":[{"award-number":["HEUCF180105"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2018YFC0309402"],"award-info":[{"award-number":["2018YFC0309402"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key R&D Program of China","award":["HEUCF180105"],"award-info":[{"award-number":["HEUCF180105"]}]},{"name":"National Key R&D Program of China","award":["2018YFC0309402"],"award-info":[{"award-number":["2018YFC0309402"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Sensors"],"published-print":{"date-parts":[[2020,5,22]]},"abstract":"\n Due to the importance of underwater exploration in the development and utilization of deep-sea resources, underwater autonomous operation is more and more important to avoid the dangerous high-pressure deep-sea environment. For underwater autonomous operation, the intelligent computer vision is the most important technology. In an underwater environment, weak illumination and low-quality image enhancement, as a preprocessing procedure, is necessary for underwater vision. In this paper, a combination of max-RGB method and shades of gray method is applied to achieve the enhancement of underwater vision, and then a CNN (Convolutional Neutral Network) method for solving the weakly illuminated problem for underwater images is proposed to train the mapping relationship to obtain the illumination map. After the image processing, a deep CNN method is proposed to perform the underwater detection and classification, according to the characteristics of underwater vision, two improved schemes are applied to modify the deep CNN structure. In the first scheme, a\n \n 1<\/mml:mn>\n \u2217<\/mml:mo>\n 1<\/mml:mn>\n <\/mml:math>\n convolution kernel is used on the\n \n 26<\/mml:mn>\n \u2217<\/mml:mo>\n 26<\/mml:mn>\n <\/mml:math>\n feature map, and then a downsampling layer is added to resize the output to equal\n \n 13<\/mml:mn>\n \u2217<\/mml:mo>\n 13<\/mml:mn>\n <\/mml:math>\n . In the second scheme, a downsampling layer is added firstly, and then the convolution layer is inserted in the network, the result is combined with the last output to achieve the detection. Through comparison with the Fast RCNN, Faster RCNN, and the original YOLO V3, scheme 2 is verified to be better in detecting underwater objects. The detection speed is about 50\u2009FPS (Frames per Second), and mAP (mean Average Precision) is about 90%. The program is applied in an underwater robot; the real-time detection results show that the detection and classification are accurate and fast enough to assist the robot to achieve underwater working operation.\n <\/jats:p>","DOI":"10.1155\/2020\/6707328","type":"journal-article","created":{"date-parts":[[2020,5,22]],"date-time":"2020-05-22T19:44:42Z","timestamp":1590176682000},"page":"1-20","source":"Crossref","is-referenced-by-count":146,"title":["Underwater Image Processing and Object Detection Based on Deep CNN Method"],"prefix":"10.1155","volume":"2020","author":[{"given":"Fenglei","family":"Han","sequence":"first","affiliation":[{"name":"College of Shipbuilding Engineering, Harbin Engineering University, No. 145 Nantong Street, NanGang District, Harbin, Heilongjiang Province 150001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9582-2028","authenticated-orcid":true,"given":"Jingzheng","family":"Yao","sequence":"additional","affiliation":[{"name":"College of Shipbuilding Engineering, Harbin Engineering University, No. 145 Nantong Street, NanGang District, Harbin, Heilongjiang Province 150001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haitao","family":"Zhu","sequence":"additional","affiliation":[{"name":"College of Shipbuilding Engineering, Harbin Engineering University, No. 145 Nantong Street, NanGang District, Harbin, Heilongjiang Province 150001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunhui","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Shipbuilding Engineering, Harbin Engineering University, No. 145 Nantong Street, NanGang District, Harbin, Heilongjiang Province 150001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","reference":[{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/0016-0032(80)90058-7"},{"issue":"9","key":"3","first-page":"2207","volume":"16","year":"2010","journal-title":"IEEE Transactions on Image Processing"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1016\/S0146-664X(77)80011-7"},{"key":"5","year":"1994"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2015.08.033"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1117\/1.JEI.24.3.033023"},{"issue":"1","key":"8","first-page":"99","volume":"2165","year":"2007","journal-title":"Journal of Intelligent Systems"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1038\/scientificamerican1277-108"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.4031\/002533205787442576"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2008.2006658"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2012.2202675"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1109\/JOE.2012.2229066"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1364\/AO.42.002794"},{"key":"23","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"25","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2389824"},{"key":"28","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2016.2577031"},{"key":"32","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2018.01.010"},{"key":"34","doi-asserted-by":"publisher","DOI":"10.1109\/83.597272"},{"key":"35","year":"2017"}],"container-title":["Journal of Sensors"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/js\/2020\/6707328.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/js\/2020\/6707328.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/js\/2020\/6707328.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,22]],"date-time":"2020-05-22T19:44:48Z","timestamp":1590176688000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/js\/2020\/6707328\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,22]]},"references-count":19,"alternative-id":["6707328","6707328"],"URL":"https:\/\/doi.org\/10.1155\/2020\/6707328","relation":{},"ISSN":["1687-725X","1687-7268"],"issn-type":[{"value":"1687-725X","type":"print"},{"value":"1687-7268","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,22]]}}}