A Review on Computer Vision - Scene Classification Techniques

Aayushi A. Shah, Keyur Rana
{"title":"A Review on Computer Vision - Scene Classification Techniques","authors":"Aayushi A. Shah, Keyur Rana","doi":"10.1109/ICISC44355.2019.9036472","DOIUrl":null,"url":null,"abstract":"In today's era, need for automatic response of machines on certain task has been prevalent. Humans want their life easier and automatic in every possible way. However, those tasks require better understanding by the machine to perform human like tasks. Tasks like classification, detection and localization are on high demand and dominant research area. These tasks fall into a domain called computer vision where computers by analyzing and understanding performs human like tasks. This domain provides the automatic inference by machines to make human life easier. In this paper, we focus on one of the difficult computer vision tasks called scene classification. Scene Classification deals with techniques that make machine intelligent and automated by processing given input say image. As machines are made automatic and intelligent to perform various tasks, Artificial Intelligence and Image processing comes into the picture. We study and analyze various approaches and methods by which such task can be handled easily and accurately. Furthermore, we compare all the approaches and find out the best approach to opt for this task.","PeriodicalId":419157,"journal":{"name":"2019 Third International Conference on Inventive Systems and Control (ICISC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Third International Conference on Inventive Systems and Control (ICISC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISC44355.2019.9036472","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

In today's era, need for automatic response of machines on certain task has been prevalent. Humans want their life easier and automatic in every possible way. However, those tasks require better understanding by the machine to perform human like tasks. Tasks like classification, detection and localization are on high demand and dominant research area. These tasks fall into a domain called computer vision where computers by analyzing and understanding performs human like tasks. This domain provides the automatic inference by machines to make human life easier. In this paper, we focus on one of the difficult computer vision tasks called scene classification. Scene Classification deals with techniques that make machine intelligent and automated by processing given input say image. As machines are made automatic and intelligent to perform various tasks, Artificial Intelligence and Image processing comes into the picture. We study and analyze various approaches and methods by which such task can be handled easily and accurately. Furthermore, we compare all the approaches and find out the best approach to opt for this task.
计算机视觉场景分类技术综述
在当今时代,对某些任务的机器自动响应的需求已经普遍存在。人类希望他们的生活在每一个可能的方式更轻松和自动化。然而,这些任务需要机器更好地理解才能执行类似人类的任务。分类、检测和定位等任务是高需求和主导的研究领域。这些任务属于计算机视觉领域,计算机通过分析和理解执行类似人类的任务。这个领域提供了机器的自动推理,使人类的生活更轻松。在本文中,我们重点研究了一个困难的计算机视觉任务,即场景分类。场景分类是通过处理给定的输入图像,使机器智能化和自动化的技术。随着机器实现自动化和智能化,可以执行各种任务,人工智能和图像处理开始出现。我们研究和分析各种途径和方法,使这些任务能够容易和准确地处理。此外,我们比较了所有的方法,找出了选择这个任务的最佳方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信