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Iet Biometrics SCIE

国际简称:IET BIOMETRICS  参考译名:生物识别

主要研究方向:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE  非预警期刊  审稿周期: 33 Weeks

《生物识别》(Iet Biometrics)是一本由Wiley出版的以COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE为研究特色的国际期刊,发表该领域相关的原创研究文章、评论文章和综述文章,及时报道该领域相关理论、实践和应用学科的最新发现,旨在促进该学科领域科学信息的快速交流。该期刊是一本开放期刊,近三年没有被列入预警名单。

  • 4区 中科院分区
  • Q3 JCR分区
  • 18 年发文量
  • 1.8 IF影响因子
  • 开放 是否OA
  • 19 H-index
  • 2012 创刊年份
  • Bi-monthly 出版周期
  • English 出版语言

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

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Iet Biometrics期刊信息

  • ISSN:2047-4938
  • 出版语言:English
  • 是否OA:开放
  • E-ISSN:2047-4946
  • 出版地区:USA
  • 是否预警:
  • 出版商:Wiley
  • 出版周期:Bi-monthly
  • 创刊时间:2012
  • 开源占比:0.5748
  • Gold OA文章占比:75.93%
  • OA被引用占比:0.0503...
  • 出版国人文章占比:0.1
  • 出版撤稿占比:0
  • 研究类文章占比:94.44%

Iet Biometrics CiteScore评价数据(2024年最新版)

CiteScore SJR SNIP CiteScore 指数
5.9 0.583 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%

名词解释:CiteScore 是衡量期刊所发表文献的平均受引用次数,是在 Scopus 中衡量期刊影响力的另一个指标。当年CiteScore 的计算依据是期刊最近4年(含计算年度)的被引次数除以该期刊近四年发表的文献数。例如,2022年的 CiteScore 计算方法为:2022年的 CiteScore =2019-2022年收到的对2019-2022年发表的文件的引用数量÷2019-2022年发布的文献数量 注:文献类型包括:文章、评论、会议论文、书籍章节和数据论文。

Iet Biometrics中科院评价数据

中科院 2023年12月升级版

Top期刊 综述期刊 大类学科 小类学科
计算机科学 4区 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机:人工智能 4区

中科院 2022年12月升级版

Top期刊 综述期刊 大类学科 小类学科
计算机科学 3区 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机:人工智能 4区

中科院 2021年12月旧的升级版

Top期刊 综述期刊 大类学科 小类学科
计算机科学 3区 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机:人工智能 4区

中科院 2021年12月基础版

Top期刊 综述期刊 大类学科 小类学科
工程技术 4区 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机:人工智能 4区

中科院 2021年12月升级版

Top期刊 综述期刊 大类学科 小类学科
计算机科学 3区 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机:人工智能 4区

中科院 2020年12月旧的升级版

Top期刊 综述期刊 大类学科 小类学科
计算机科学 4区 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机:人工智能 4区

Iet Biometrics JCR评价数据(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%

Iet Biometrics历年数据统计

影响因子
中科院分区

Iet Biometrics同类期刊

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