北京交通大学学报2016，Vol.40Issue(4)：82-91,10.DOI:10.11860/j.issn.1673-0291.2016.04.013
基于DCNN的图像语义分割综述
A review on image semantic segmentation based on DCNN
摘要
Abstract
Image semantic segmentation is one of the most important problems in computer vision, whose target is to assign a semantic label for each pixel of a given image and segment the image into several visually meaningful or interest regions,in order for the image analysis and vision un-derstanding .In recent years,tremendous progress has been made for semantic segmentation due to the development of deep convolutional neural network (DCNN).In this paper,we firstly dis-cuss the difficulties and challenges of semantic segmentation.Then,DCNN-based achievements in the study of semantic segmentation are reviewed.In addition,an analysis for semantic segmen-tation based on PASCAL VOC dataset is given,which is generally acknowledged as a popular public evaluation for semantic segmentation.Finally,some probable development directions of semantic segmentation are discussed.关键词
图像语义分割/深度学习/深度卷积神经网络Key words
image semantic segmentation/deep learning/deep convolutional neural network分类
信息技术与安全科学引用本文复制引用
魏云超,赵耀..基于DCNN的图像语义分割综述[J].北京交通大学学报,2016,40(4):82-91,10.基金项目
国家科技重大专项资金资助(2016YFB0800404) （2016YFB0800404）
