分割
计算机科学
深度学习
人工智能
分类
领域(数学)
任务(项目管理)
机器学习
自然语言处理
数学
管理
纯数学
经济
作者
Shijie Hao,Yuan Zhou,Yanrong Guo
出处
期刊:Neurocomputing
[Elsevier BV]
日期:2020-04-13
卷期号:406: 302-321
被引量:544
标识
DOI:10.1016/j.neucom.2019.11.118
摘要
Semantic segmentation is a challenging task in computer vision. In recent years, the performance of semantic segmentation has been greatly improved by using deep learning techniques. A large number of novel methods have been proposed. This paper aims to provide a brief review of research efforts on deep-learning-based semantic segmentation methods. We categorize the related research according to its supervision level, i.e., fully-supervised methods, weakly-supervised methods and semi-supervised methods. We also discuss the common challenges of the current research, and present several valuable growing research points in this field. This survey is expected to familiarize readers with the progress and challenges of semantic segmentation research in the deep learning era.
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