{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T01:29:20Z","timestamp":1769909360243,"version":"3.49.0"},"reference-count":32,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2019,5,14]],"date-time":"2019-05-14T00:00:00Z","timestamp":1557792000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Science Foundation of China (NSFC)","award":["No. 51579204"],"award-info":[{"award-number":["No. 51579204"]}]},{"name":"Wuhan University of Technology Independent Innovation Research Foundation of China","award":["No. 2018\u2162059GX"],"award-info":[{"award-number":["No. 2018\u2162059GX"]}]},{"name":"Virginia Microelectronics Consortium (VMEC)","award":["2019-01-01"],"award-info":[{"award-number":["2019-01-01"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Robust detection and recognition of water surfaces are critical for autonomous navigation of unmanned surface vehicles (USVs), since any none-water region is likely an obstacle posing a potential danger to the sailing vehicle. A novel water region visual detection method is proposed in this paper. First, the input image pixels are clustered into different regions and each pixel is assigned a label tag and a confidence value by adaptive multistage segmentation algorithm. Then the resulting label map and associated confidence map are fed into a convolutional neural network (CNN) as training samples to train the network online. Finally, the online trained CNN is used to segment the input image again but with greater precision and stronger robustness. Compared with other deep-learning image segmentation algorithms, the proposed method has two advantages. Firstly, it dispenses with the need of manual labeling training samples which is a costly and painful task. Secondly, it allows real-time online training for CNN, making the network adaptive to the navigational environment. Another contribution of this work relates to the training process of neuro network. An effective network training method is designed to learn from the imperfect training data. We present the experiments in the lake with a various scene and demonstrate that our proposed method could be applied to recognize the water region in the unknown navigation environment automatically.<\/jats:p>","DOI":"10.3390\/s19102216","type":"journal-article","created":{"date-parts":[[2019,5,14]],"date-time":"2019-05-14T10:42:33Z","timestamp":1557830553000},"page":"2216","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":43,"title":["Autonomous Visual Perception for Unmanned Surface Vehicle Navigation in an Unknown Environment"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9003-0478","authenticated-orcid":false,"given":"Wenqiang","family":"Zhan","sequence":"first","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan 430063, China"},{"name":"Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA 22030, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changshi","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan 430063, China"},{"name":"Hubei Key Laboratory of Inland Shipping Technology, Wuhan University of Technology, Wuhan 430063, China"},{"name":"National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan 430063, China"},{"name":"Institute of Ocean Information Technology, Shandong Jiaotong University, Weihai 250357, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanqiao","family":"Wen","sequence":"additional","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan 430063, China"},{"name":"Hubei Key Laboratory of Inland Shipping Technology, Wuhan University of Technology, Wuhan 430063, China"},{"name":"National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan 430063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunhui","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan 430063, China"},{"name":"Hubei Key Laboratory of Inland Shipping Technology, Wuhan University of Technology, Wuhan 430063, China"},{"name":"National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan 430063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5609-4558","authenticated-orcid":false,"given":"Haiwen","family":"Yuan","sequence":"additional","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan 430063, China"},{"name":"School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Supu","family":"Xiu","sequence":"additional","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan 430063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6885-5449","authenticated-orcid":false,"given":"Yimeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan 430063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiong","family":"Zou","sequence":"additional","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan 430063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Ocean Information Technology, Shandong Jiaotong University, Weihai 250357, China"},{"name":"School of Transportation, Wuhan University of Technology, Wuhan 430063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiliang","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA 22030, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Matos, A., Martins, A., Dias, A., Ferreira, B., Almeida, J.M., Ferreira, H., Amaral, G., Figueiredo, A., Almeida, R., and Silva, F. 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