图像处理中基于深度学习的图像语义分割综述

A Review of Semantic Image Segmentation Based on Deep Learning in Image Processing

图像语义分割(Semantic Segmentation)是计算机视觉领域的研究热点,图像语义分割不仅能预测一幅图像中的不同类别,同时还能定位不同语义类别的位置,具有重要的研究意义和应用价值。这些方法被用于人工智能当中,应用于无人驾驶、遥感影像检测、医疗影像等研究领域。全卷积神经网络的快速崛起推动了图像语义分割领域的发展,二者的融合取得了显著的成就。主要从语义分割的介绍出发,对近几年的代表性工作进行了阐述,并对未来的研究方向进行展望。

Semantic image segmentation is a hot research topic in the field of computer vision.,and it not only pre⁃dicts different categories in an image,but also locates the location of different semantic categories,which has impor⁃tant research significance and application value.This method is used is artificial intelligence,unmanned driving,re⁃mote sensing image detection,medical image research and other aspects.The rapid rise of the fully-convolutional neural network has propelled the development of the semantic image segmentation field,and the integration of the two has achieved remarkable accomplishments.This paper will start from the introduction of semantic segmenta⁃tion,expound representative work in recent years,and look forward to future research directions.