期刊中文名:生物识别ISSN:2047-4938E-ISSN:2047-4946
该杂志国际简称:IET BIOMETRICS,是由出版商Wiley出版的一本致力于发布计算机科学研究新成果的的专业学术期刊。该杂志以COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE研究为重点,主要发表刊登有创见的学术论文文章、行业最新科研成果,扼要报道阶段性研究成果和重要研究工作的最新进展,选载对学科发展起指导作用的综述与专论,促进学术发展,为广大读者服务。该刊是一本国际优秀杂志,在国际上有很高的学术影响力。
《Iet Biometrics》是一本以English为主的开放获取国际优秀期刊,中文名称生物识别,本刊主要出版、报道计算机科学-COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE领域的研究动态以及在该领域取得的各方面的经验和科研成果,介绍该领域有关本专业的最新进展,探讨行业发展的思路和方法,以促进学术信息交流,提高行业发展。该刊已被国际权威数据库SCIE收录,为该领域相关学科的发展起到了良好的推动作用,也得到了本专业人员的广泛认可。该刊最新影响因子为1.8,最新CiteScore 指数为5.9。
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
2023年12月升级版 |
综述:否
TOP期刊:否
大类:计算机科学 4区
小类:
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE |
2022年12月升级版 |
综述:否
TOP期刊:否
大类:计算机科学 3区
小类:
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE |
2021年12月旧的升级版 |
综述:否
TOP期刊:否
大类:计算机科学 3区
小类:
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE |
2021年12月基础版 |
综述:否
TOP期刊:否
大类:工程技术 4区
小类:
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE |
2021年12月升级版 |
综述:否
TOP期刊:否
大类:计算机科学 3区
小类:
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE |
2020年12月旧的升级版 |
综述:否
TOP期刊:否
大类:计算机科学 4区
小类:
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE |
中科院SCI分区:是中国科学院文献情报中心科学计量中心的科学研究成果。期刊分区表自2004年开始发布,延续至今;2019年推出升级版,实现基础版、升级版并存过渡,2022年只发布升级版,期刊分区表数据每年底发布。 中科院分区为4个区。中科院分区采用刊物前3年影响因子平均值进行分区,即前5%为该类1区,6%~20%为2区、21%~50%为3区,其余的为4区。1区和2区杂志很少,杂志质量相对也高,基本都是本领域的顶级期刊。
按JIF指标学科分区 |
学科:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
收录子集:SCIE
分区:Q3
排名:136 / 197
百分位:
31.2% |
按JCI指标学科分区 |
学科:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
收录子集:SCIE
分区:Q4
排名:152 / 198
百分位:
23.48% |
JCR分区:JCR分区来自科睿唯安公司,JCR是一个独特的多学科期刊评价工具,为唯一提供基于引文数据的统计信息的期刊评价资源。每年发布的JCR分区,设置了254个具体学科。JCR分区根据每个学科分类按照期刊当年的影响因子高低将期刊平均分为4个区,分别为Q1、Q2、Q3和Q4,各占25%。JCR分区中期刊的数量是均匀分为四个部分的。
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% |
该杂志是一本国际优秀杂志,在国际上有较高的学术影响力,行业关注度很高,已被国际权威数据库SCIE收录,该杂志在COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE综合专业领域专业度认可很高,对稿件内容的创新性和学术性要求很高,作为一本国际优秀杂志,一般投稿过审时间都较长,投稿过审时间平均 33 Weeks ,如果想投稿该刊要做好时间安排。版面费不祥。该杂志近两年未被列入预警名单,建议您投稿。如您想了解更多投稿政策及投稿方案,请咨询客服。
若用户需要出版服务,请联系出版商:WILEY, 111 RIVER ST, HOBOKEN, USA, NJ, 07030-5774。
COMPUTER SCIENCE, INFORMATION SYSTEMS
中科院 3区
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
中科院 3区
AUTOMATION & CONTROL SYSTEMS
中科院 4区
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
中科院 1区
ENGINEERING, ELECTRICAL & ELECTRONIC
中科院 4区
ENGINEERING, ELECTRICAL & ELECTRONIC
中科院 3区
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
中科院 4区
ACOUSTICS
中科院 3区