Research of Self-Attention in Image Segmentation

被引：1

作者：

Cao, Fude ^{[1
]}

Zheng, Chunguang ^{[1
]}

Huang, Limin ^{[1
]}

Wang, Aihua ^{[1
]}

Zhang, Jiong ^{[1
]}

Zhou, Feng ^{[1
]}

Ju, Haoxue ^{[1
]}

Guo, Haitao ^{[1
]}

Du, Yuxia ^{[1
]}

机构：

[1] Shandong Inst Commerce & Technol, Jinan, Shandong, Peoples R China

来源：

JOURNAL OF INFORMATION TECHNOLOGY RESEARCH | 2022年 / 15卷 / 01期

关键词：

Convolutional Neural Networks; Image Segmentation; Self-Attention;

D O I：

10.4018/JITR.298619

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Although the traditional convolutional neural network is applied to image segmentation successfully, it has some limitations. That's the context information of the long-range on the image is not well captured. With the success of the introduction of self-attentional mechanisms in the field of natural language processing (NLP), people have tried to introduce the attention mechanism in the field of computer vision. It turns out that self-attention can really solve this long-range dependency problem. This paper is a summary on the application of self-attention to image segmentation in the past two years.

引用

页数：12

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