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dc.contributor.advisor李翠华
dc.contributor.author王冰
dc.date.accessioned2018-12-05T01:48:13Z
dc.date.available2018-12-05T01:48:13Z
dc.date.issued2018-01-02
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/170641
dc.description.abstract目前,深度学习已经在多个领域取得突破,然而,将深度学习用于舰船目标检测方面的研究和应用还比较少。其中,一个关键的问题是样本集建立困难,目前尚无公开可用的舰船目标检测数据集。另一方面,目前用于舰船目标检测的方法大多为传统方法,如HOG+SVM、DPM等,这些方法对光照、形态变化、遮挡等鲁棒性不强,并且检测精度和实时性方面远比不上近些年来越来越受关注的深度学习方法。本文针对以上两个问题,做了以下几个方面的工作: 1.针对舰船目标样本难问题:人工建立了舰船目标检测数据集,包含8526张船样本(带标注),并把该样本集中的2458张样本细分为包括军舰、民船在内的9大类。此外,为了研究在复杂背景下小目标...
dc.description.abstractAt present, deep learning has made breakthroughs in many fields. The current research and application of deep learning in ship detetion is still relatively little. One of the difficulties in ship detection is that there is no publicly available dataset of the ships. Another problem is that current methods for the ship detection are mostly traditional detection methods, such as HOG + SVM, DPM, etc....
dc.language.isozh_CN
dc.relation.urihttps://catalog.xmu.edu.cn/opac/openlink.php?strText=58824&doctype=ALL&strSearchType=callno
dc.source.urihttps://etd.xmu.edu.cn/detail.asp?serial=60442
dc.subject舰船检测
dc.subject深度学习
dc.subject舰船数据集
dc.subjectShip Detection
dc.subjectDeep Learning
dc.subjectShip Datasets
dc.title基于深度学习的舰船目标检测研究
dc.title.alternativeResearch on Deep Learning-based Ship Detection
dc.typethesis
dc.date.replied2017-05-14
dc.description.note学位:工学硕士
dc.description.note院系专业:信息科学与技术学院_工程硕士(计算机技术)
dc.description.note学号:23020141153199


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