基于深度学习的图像语义分割技术综述

图像分割是计算机视觉领域的一个重要方向，是图像处理的核心环节。伴随深度学习技术的发展，结合深度学习的图像分割技术在精确度上远超传统图像分割方法。卷积神经网络（CNN）与全卷积神经网络（FCN）的提出极大促进了图像语义分割技术发展，研究人员提出了很多新型网络模型，分割精准度大幅度提升。从传统语义分割方法、深度学习与传统方法相结合的图像语义分割、基于深度学习的语义分割3个方面阐述图像语义分割技术研究进展，为基于深度学习的图像语义分割技术研究提供参考。

A Review of Image Semantic Segmentation Based on Deep Learning

Image segmentation is an important direction in computer vision and the core of image processing.With the development of deep learning technology， image segmentation combined with deep learning is far more accurate than traditional image segmentation methods.The proposal of CNN and FCN has greatly promoted the development of image semantic segmentation technology， and researchers proposed many new network models， which greatly improved the segmentation accuracy.This paper expounds the research progress of image semantic segmentation technology from three aspects： the traditional semantic segmentation method， the image semantic segmentation combining deep learning and traditional methods， and the semantic segmentation based on deep learning， so as to provide references for the research of image semantic segmentation technology based on deep learning.