Review on Image Scene Classification Technology

TIAN Yan-ling; ZHANG Wei-tong; ZHANG Qie-shi; LU Gang; WU Xiao-jun

doi:10.3969/j.issn.0372-2112.2019.04.020

您当前的位置：

首页 >

文章列表页 >

Review on Image Scene Classification Technology

更新时间：2025-07-16

- Review on Image Scene Classification Technology
- Acta Electronica Sinica Vol. 47, Issue 4, Pages: 915-926(2019)
- 作者机构：
  
  1. 陕西师范大学现代教学技术教育部重点实验室,陕西,西安,710062
  2. 陕西师范大学计算机科学学院,陕西,西安,710062
  3. 中国科学院深圳先进技术研究院,广东,深圳,518055
  4. 陕西师范大学现代教学技术教育部重点实验室,陕西,西安,710062
  5. 陕西师范大学计算机科学学院,陕西,西安,710062
  6. 中国科学院深圳先进技术研究院,广东,深圳,518055
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2019.04.020
  CLC： TP391
- Published Online：25 April 2019，
  
  Published：2019
- 稿件说明：
移动端阅览
TIAN Yan-ling, ZHANG Wei-tong, ZHANG Qie-shi, et al. Review on Image Scene Classification Technology[J]. Acta Electronica Sinica, 2019, 47(4): 915-926.
DOI：

TIAN Yan-ling, ZHANG Wei-tong, ZHANG Qie-shi, et al. Review on Image Scene Classification Technology[J]. Acta Electronica Sinica, 2019, 47(4): 915-926. DOI： 10.3969/j.issn.0372-2112.2019.04.020.

摘要

目前，基于计算机视觉分析的图像场景分类技术已被广泛研究并应用在众多学科领域中.本文从不同角度对近年来典型的场景分类技术进行了深入的探讨与比较.首先介绍了场景分类技术的背景、应用场景以及发展现状；然后基于特征提取、语义分析和机器学习的角度分别对国内外的相关研究进行系统的分析、比较及总结；最后对目前研究所面临的问题和未来技术的发展给出总结与展望.

Abstract

The computer vision based scene classification technology is widely developed and applied in different fields.In this paper

the typical scene classification technology is analyzed and compared from the different directions.First

the background

application and development situation is introduced.Then

the related researches both at home and overseas are analyzed

compared and summarized from the perspectives of feature extraction

semantic analysis and machine learning.Finally

the problems that the current researches are facing and potential future development are discussed.

关键词

Keywords

references

Views

998

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Research on the Generation of Adversarial Samples Based on the Attribution of Principal Features

An Optimized Sparse Auto-encoder Network Based on Feature Clustering

Abnormal Event Detection Based on Deep Learning

Survey of Object Detection Based on Deep Learning

Related Author

WANG Shuo

XU Ru-zhi

GUAN Zhi-tao

FU Xiao

SHEN Yuan-tong

FU Li-hua

YANG Di-wei

WEN Jia

Related Institution

School of Control and Computer Engineering， North China Electric Power University

College of Mathematics and Physics, China University of Geosciences

School of Information Science and Engineering, Yanshan University

The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province

State Key Laboratory of Software Engineering of Hebei Province

⁰