@article{oai:kyutech.repo.nii.ac.jp:00004728,
 author = {丹, 康弘 and Tan, Yasuhiro and Tan, Joo kooi and タン, ジュークイ and Kim, Hyungseop and 金, 亨燮 and 石川, 聖二 and Ishikawa, Seiji},
 journal = {日本船舶海洋工学会論文集, Journal of the Japan Society of Naval Architects and Ocean Engineers},
 month = {Mar},
 note = {Side-scan and forward looking sonars are some of the most widely used imaging systems for obtaining large scale images of a seafloor, and their use continues to expand rapidly with their increasing deployment on Autonomous Underwater Vehicles. However, it is difficult to extract quantitative information from the images generated from these processes, in particular, for the detection and extraction of information on the objects within these images. We propose in this paper an algorithm for automatic detection of underwater objects in side-scan images based on machine learning employing adaptive boosting. Experimental results show that the method produces consistent maps of a seafloor.},
 pages = {115--121},
 title = {ブースティングによる機械学習に基づく海底物体の検出},
 volume = {18},
 year = {2014}
}