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Iet Computer Vision

Iet Computer VisionSCIE

国际简称:IET COMPUT VIS  参考译名:计算机视觉

  • 中科院分区

    4区

  • CiteScore分区

    Q3

  • JCR分区

    Q3

基本信息:
ISSN:1751-9632
E-ISSN:1751-9640
是否OA:开放
是否预警:否
TOP期刊:否
出版信息:
出版地区:ENGLAND
出版商:Wiley
出版语言:English
出版周期:Bi-monthly
出版年份:2007
研究方向:工程技术-工程:电子与电气
评价信息:
影响因子:1.5
H-index:29
CiteScore指数:3.3
SJR指数:0.443
SNIP指数:0.55
发文数据:
Gold OA文章占比:84.81%
研究类文章占比:97.75%
年发文量:89
自引率:0.1176...
开源占比:0.5459
出版撤稿占比:0
出版国人文章占比:0.42
OA被引用占比:0.0206...
英文简介 期刊介绍 CiteScore数据 中科院SCI分区 JCR分区 发文数据 常见问题

英文简介Iet Computer Vision期刊介绍

IET Computer Vision seeks original research papers in a wide range of areas of computer vision. The vision of the journal is to publish the highest quality research work that is relevant and topical to the field, but not forgetting those works that aim to introduce new horizons and set the agenda for future avenues of research in computer vision.

IET Computer Vision welcomes submissions on the following topics:

Biologically and perceptually motivated approaches to low level vision (feature detection, etc.);

Perceptual grouping and organisation

Representation, analysis and matching of 2D and 3D shape

Shape-from-X

Object recognition

Image understanding

Learning with visual inputs

Motion analysis and object tracking

Multiview scene analysis

Cognitive approaches in low, mid and high level vision

Control in visual systems

Colour, reflectance and light

Statistical and probabilistic models

Face and gesture

Surveillance

Biometrics and security

Robotics

Vehicle guidance

Automatic model aquisition

Medical image analysis and understanding

Aerial scene analysis and remote sensing

Deep learning models in computer vision

Both methodological and applications orientated papers are welcome.

Manuscripts submitted are expected to include a detailed and analytical review of the literature and state-of-the-art exposition of the original proposed research and its methodology, its thorough experimental evaluation, and last but not least, comparative evaluation against relevant and state-of-the-art methods. Submissions not abiding by these minimum requirements may be returned to authors without being sent to review.

Special Issues Current Call for Papers:

Computer Vision for Smart Cameras and Camera Networks - https://digital-library.theiet.org/files/IET_CVI_SC.pdf

Computer Vision for the Creative Industries - https://digital-library.theiet.org/files/IET_CVI_CVCI.pdf

期刊简介Iet Computer Vision期刊介绍

《Iet Computer Vision》自2007出版以来,是一本计算机科学优秀杂志。致力于发表原创科学研究结果,并为计算机科学各个领域的原创研究提供一个展示平台,以促进计算机科学领域的的进步。该刊鼓励先进的、清晰的阐述,从广泛的视角提供当前感兴趣的研究主题的新见解,或审查多年来某个重要领域的所有重要发展。该期刊特色在于及时报道计算机科学领域的最新进展和新发现新突破等。该刊近一年未被列入预警期刊名单,目前已被权威数据库SCIE收录,得到了广泛的认可。

该期刊投稿重要关注点:

Cite Score数据(2024年最新版)Iet Computer Vision Cite Score数据

  • CiteScore:3.3
  • SJR:0.443
  • SNIP:0.55
学科类别 分区 排名 百分位
大类:Computer Science 小类:Computer Vision and Pattern Recognition Q3 56 / 106

47%

大类:Computer Science 小类:Software Q3 247 / 407

39%

CiteScore 是由Elsevier(爱思唯尔)推出的另一种评价期刊影响力的文献计量指标。反映出一家期刊近期发表论文的年篇均引用次数。CiteScore以Scopus数据库中收集的引文为基础,针对的是前四年发表的论文的引文。CiteScore的意义在于,它可以为学术界提供一种新的、更全面、更客观地评价期刊影响力的方法,而不仅仅是通过影响因子(IF)这一单一指标来评价。

历年Cite Score趋势图

中科院SCI分区Iet Computer Vision 中科院分区

中科院 2023年12月升级版 综述期刊:否 Top期刊:否
大类学科 分区 小类学科 分区
计算机科学 4区 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机:人工智能 ENGINEERING, ELECTRICAL & ELECTRONIC 工程:电子与电气 4区 4区

中科院分区表 是以客观数据为基础,运用科学计量学方法对国际、国内学术期刊依据影响力进行等级划分的期刊评价标准。它为我国科研、教育机构的管理人员、科研工作者提供了一份评价国际学术期刊影响力的参考数据,得到了全国各地高校、科研机构的广泛认可。

中科院分区表 将所有期刊按照一定指标划分为1区、2区、3区、4区四个层次,类似于“优、良、及格”等。最开始,这个分区只是为了方便图书管理及图书情报领域的研究和期刊评估。之后中科院分区逐步发展成为了一种评价学术期刊质量的重要工具。

历年中科院分区趋势图

JCR分区Iet Computer Vision JCR分区

2023-2024 年最新版
按JIF指标学科分区 收录子集 分区 排名 百分位
学科:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE SCIE Q4 154 / 197

22.1%

学科:ENGINEERING, ELECTRICAL & ELECTRONIC SCIE Q3 252 / 352

28.6%

按JCI指标学科分区 收录子集 分区 排名 百分位
学科:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE SCIE Q4 156 / 198

21.46%

学科:ENGINEERING, ELECTRICAL & ELECTRONIC SCIE Q4 267 / 354

24.72%

JCR分区的优势在于它可以帮助读者对学术文献质量进行评估。不同学科的文章引用量可能存在较大的差异,此时单独依靠影响因子(IF)评价期刊的质量可能是存在一定问题的。因此,JCR将期刊按照学科门类和影响因子分为不同的分区,这样读者可以根据自己的研究领域和需求选择合适的期刊。

历年影响因子趋势图

发文数据

2023-2024 年国家/地区发文量统计
  • 国家/地区数量
  • CHINA MAINLAND158
  • India24
  • USA23
  • England20
  • Italy16
  • Turkey15
  • Iran12
  • South Korea12
  • France9
  • Pakistan8

本刊中国学者近年发表论文

  • 1、Cross-modality person re-identification using hybrid mutual learning

    Author: Zhang, Zhong; Dong, Qing; Wang, Sen; Liu, Shuang; Xiao, Baihua; Durrani, Tariq S.

    Journal: IET COMPUTER VISION. 2023; Vol. 17, Issue 1, pp. 1-12. DOI: 10.1049/cvi2.12123

  • 2、Elastic temporal alignment for few-shot action recognition

    Author: Pan, Fei; Xu, Chunlei; Zhang, Hongjie; Guo, Jie; Guo, Yanwen

    Journal: IET COMPUTER VISION. 2023; Vol. 17, Issue 1, pp. 39-50. DOI: 10.1049/cvi2.12127

  • 3、MFNet: Panoptic segmentation network based on multiscale feature weighted fusion and frequency domain attention mechanism

    Author: Lei, Haiwei; He, Fangyuan; Jia, Bohui; Wu, Qian

    Journal: IET COMPUTER VISION. 2023; Vol. 17, Issue 1, pp. 88-97. DOI: 10.1049/cvi2.12133

  • 4、Integration graph attention network and multi-centre constrained loss for cross-modality person re-identification

    Author: He, Di; Zhang, Jingrui; Zhang, Zhong; Liu, Shuang; Durrani, Tariq S.

    Journal: IET COMPUTER VISION. 2023; Vol. 17, Issue 1, pp. 76-87. DOI: 10.1049/cvi2.12132

  • 5、Multi-scale pedestrian detection with global-local attention and multi-scale receptive field context

    Author: Xue, Pan; Chen, Houjin; Li, Yanfeng; Li, Jupeng

    Journal: IET COMPUTER VISION. 2023; Vol. 17, Issue 1, pp. 13-25. DOI: 10.1049/cvi2.12125

  • 6、Multi-template temporal information fusion for Siamese object tracking

    Author: Lu, Xiaofeng; Wang, Zhengyang; Wang, Xuan; Hei, Xinhong

    Journal: IET COMPUTER VISION. 2023; Vol. 17, Issue 1, pp. 51-61. DOI: 10.1049/cvi2.12128

  • 7、Few-shot classification using Gaussianisation prototypical classifier

    Author: Liu, Fan; Li, Feifan; Yang, Sai

    Journal: IET COMPUTER VISION. 2023; Vol. 17, Issue 1, pp. 62-75. DOI: 10.1049/cvi2.12129

  • 8、Domain-specific feature recalibration and alignment for multi-source unsupervised domain adaptation

    Author: Wang, Mengzhu; Chen, Dingyao; Tan, Fangzhou; Liang, Tianyi; Lan, Long; Zhang, Xiang; Luo, Zhigang

    Journal: IET COMPUTER VISION. 2023; Vol. 17, Issue 1, pp. 26-38. DOI: 10.1049/cvi2.12126

投稿常见问题

通讯方式:WILEY, 111 RIVER ST, HOBOKEN, USA, NJ, 07030-5774。