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Iet Biometrics

Iet BiometricsSCIE

国际简称:IET BIOMETRICS  参考译名:生物识别

  • 中科院分区

    4区

  • CiteScore分区

    Q2

  • JCR分区

    Q3

基本信息:
ISSN:2047-4938
E-ISSN:2047-4946
是否OA:开放
是否预警:否
TOP期刊:否
出版信息:
出版地区:USA
出版商:Wiley
出版语言:English
出版周期:Bi-monthly
出版年份:2012
研究方向:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
评价信息:
影响因子:1.8
H-index:19
CiteScore指数:5.9
SJR指数:0.583
SNIP指数:0.957
发文数据:
Gold OA文章占比:75.93%
研究类文章占比:94.44%
年发文量:18
自引率:0
开源占比:0.5748
出版撤稿占比:0
出版国人文章占比:0.1
OA被引用占比:0.0503...
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 Biometrics期刊介绍

The field of biometric recognition - automated recognition of individuals based on their behavioural and biological characteristics - has now reached a level of maturity where viable practical applications are both possible and increasingly available. The biometrics field is characterised especially by its interdisciplinarity since, while focused primarily around a strong technological base, effective system design and implementation often requires a broad range of skills encompassing, for example, human factors, data security and database technologies, psychological and physiological awareness, and so on. Also, the technology focus itself embraces diversity, since the engineering of effective biometric systems requires integration of image analysis, pattern recognition, sensor technology, database engineering, security design and many other strands of understanding.

The scope of the journal is intentionally relatively wide. While focusing on core technological issues, it is recognised that these may be inherently diverse and in many cases may cross traditional disciplinary boundaries. The scope of the journal will therefore include any topics where it can be shown that a paper can increase our understanding of biometric systems, signal future developments and applications for biometrics, or promote greater practical uptake for relevant technologies:

Development and enhancement of individual biometric modalities including the established and traditional modalities (e.g. face, fingerprint, iris, signature and handwriting recognition) and also newer or emerging modalities (gait, ear-shape, neurological patterns, etc.)

Multibiometrics, theoretical and practical issues, implementation of practical systems, multiclassifier and multimodal approaches

Soft biometrics and information fusion for identification, verification and trait prediction

Human factors and the human-computer interface issues for biometric systems, exception handling strategies

Template construction and template management, ageing factors and their impact on biometric systems

Usability and user-oriented design, psychological and physiological principles and system integration

Sensors and sensor technologies for biometric processing

Database technologies to support biometric systems

Implementation of biometric systems, security engineering implications, smartcard and associated technologies in implementation, implementation platforms, system design and performance evaluation

Trust and privacy issues, security of biometric systems and supporting technological solutions, biometric template protection

Biometric cryptosystems, security and biometrics-linked encryption

Links with forensic processing and cross-disciplinary commonalities

Core underpinning technologies (e.g. image analysis, pattern recognition, computer vision, signal processing, etc.), where the specific relevance to biometric processing can be demonstrated

Applications and application-led considerations

Position papers on technology or on the industrial context of biometric system development

Adoption and promotion of standards in biometrics, improving technology acceptance, deployment and interoperability, avoiding cross-cultural and cross-sector restrictions

Relevant ethical and social issues

期刊简介Iet Biometrics期刊介绍

《Iet Biometrics》自2012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 Biometrics Cite Score数据

  • CiteScore:5.9
  • SJR:0.583
  • SNIP:0.957
学科类别 分区 排名 百分位
大类:Computer Science 小类:Signal Processing Q2 41 / 131

69%

大类:Computer Science 小类:Computer Vision and Pattern Recognition Q2 34 / 106

68%

大类:Computer Science 小类:Software Q2 143 / 407

64%

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 Biometrics 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 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 Biometrics 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 Q3 136 / 197

31.2%

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 152 / 198

23.48%

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
  • India27
  • CHINA MAINLAND23
  • USA16
  • England12
  • GERMANY (FED REP GER)12
  • Turkey11
  • Spain9
  • France8
  • Italy8
  • Portugal8

投稿常见问题

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