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    Iet Biometrics

    Iet BiometricsSCIE

    國(guó)際簡(jiǎn)稱:IET BIOMETRICS  參考譯名:生物識(shí)別

    • 中科院分區(qū)

      4區(qū)

    • CiteScore分區(qū)

      Q2

    • JCR分區(qū)

      Q3

    基本信息:
    ISSN:2047-4938
    E-ISSN:2047-4946
    是否OA:開放
    是否預(yù)警:否
    TOP期刊:否
    出版信息:
    出版地區(qū):USA
    出版商:Wiley
    出版語言:English
    出版周期:Bi-monthly
    出版年份:2012
    研究方向:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
    評(píng)價(jià)信息:
    影響因子:1.8
    H-index:19
    CiteScore指數(shù):5.9
    SJR指數(shù):0.583
    SNIP指數(shù):0.957
    發(fā)文數(shù)據(jù):
    Gold OA文章占比:75.93%
    研究類文章占比:94.44%
    年發(fā)文量:18
    自引率:0
    開源占比:0.5748
    出版撤稿占比:0
    出版國(guó)人文章占比:0.1
    OA被引用占比:0.0503...
    英文簡(jiǎn)介 期刊介紹 CiteScore數(shù)據(jù) 中科院SCI分區(qū) JCR分區(qū) 發(fā)文數(shù)據(jù) 常見問題

    英文簡(jiǎn)介Iet Biometrics期刊介紹

    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

    期刊簡(jiǎn)介Iet Biometrics期刊介紹

    《Iet Biometrics》自2012出版以來,是一本計(jì)算機(jī)科學(xué)優(yōu)秀雜志。致力于發(fā)表原創(chuàng)科學(xué)研究結(jié)果,并為計(jì)算機(jī)科學(xué)各個(gè)領(lǐng)域的原創(chuàng)研究提供一個(gè)展示平臺(tái),以促進(jìn)計(jì)算機(jī)科學(xué)領(lǐng)域的的進(jìn)步。該刊鼓勵(lì)先進(jìn)的、清晰的闡述,從廣泛的視角提供當(dāng)前感興趣的研究主題的新見解,或?qū)彶槎嗄陙砟硞€(gè)重要領(lǐng)域的所有重要發(fā)展。該期刊特色在于及時(shí)報(bào)道計(jì)算機(jī)科學(xué)領(lǐng)域的最新進(jìn)展和新發(fā)現(xiàn)新突破等。該刊近一年未被列入預(yù)警期刊名單,目前已被權(quán)威數(shù)據(jù)庫SCIE收錄,得到了廣泛的認(rèn)可。

    該期刊投稿重要關(guān)注點(diǎn):

    Cite Score數(shù)據(jù)(2024年最新版)Iet Biometrics Cite Score數(shù)據(jù)

    • CiteScore:5.9
    • SJR:0.583
    • SNIP:0.957
    學(xué)科類別 分區(qū) 排名 百分位
    大類:Computer Science 小類:Signal Processing Q2 41 / 131

    69%

    大類:Computer Science 小類:Computer Vision and Pattern Recognition Q2 34 / 106

    68%

    大類:Computer Science 小類:Software Q2 143 / 407

    64%

    CiteScore 是由Elsevier(愛思唯爾)推出的另一種評(píng)價(jià)期刊影響力的文獻(xiàn)計(jì)量指標(biāo)。反映出一家期刊近期發(fā)表論文的年篇均引用次數(shù)。CiteScore以Scopus數(shù)據(jù)庫中收集的引文為基礎(chǔ),針對(duì)的是前四年發(fā)表的論文的引文。CiteScore的意義在于,它可以為學(xué)術(shù)界提供一種新的、更全面、更客觀地評(píng)價(jià)期刊影響力的方法,而不僅僅是通過影響因子(IF)這一單一指標(biāo)來評(píng)價(jià)。

    歷年Cite Score趨勢(shì)圖

    中科院SCI分區(qū)Iet Biometrics 中科院分區(qū)

    中科院 2023年12月升級(jí)版 綜述期刊:否 Top期刊:否
    大類學(xué)科 分區(qū) 小類學(xué)科 分區(qū)
    計(jì)算機(jī)科學(xué) 4區(qū) COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 計(jì)算機(jī):人工智能 4區(qū)

    中科院分區(qū)表 是以客觀數(shù)據(jù)為基礎(chǔ),運(yùn)用科學(xué)計(jì)量學(xué)方法對(duì)國(guó)際、國(guó)內(nèi)學(xué)術(shù)期刊依據(jù)影響力進(jìn)行等級(jí)劃分的期刊評(píng)價(jià)標(biāo)準(zhǔn)。它為我國(guó)科研、教育機(jī)構(gòu)的管理人員、科研工作者提供了一份評(píng)價(jià)國(guó)際學(xué)術(shù)期刊影響力的參考數(shù)據(jù),得到了全國(guó)各地高校、科研機(jī)構(gòu)的廣泛認(rèn)可。

    中科院分區(qū)表 將所有期刊按照一定指標(biāo)劃分為1區(qū)、2區(qū)、3區(qū)、4區(qū)四個(gè)層次,類似于“優(yōu)、良、及格”等。最開始,這個(gè)分區(qū)只是為了方便圖書管理及圖書情報(bào)領(lǐng)域的研究和期刊評(píng)估。之后中科院分區(qū)逐步發(fā)展成為了一種評(píng)價(jià)學(xué)術(shù)期刊質(zhì)量的重要工具。

    歷年中科院分區(qū)趨勢(shì)圖

    JCR分區(qū)Iet Biometrics JCR分區(qū)

    2023-2024 年最新版
    按JIF指標(biāo)學(xué)科分區(qū) 收錄子集 分區(qū) 排名 百分位
    學(xué)科:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE SCIE Q3 136 / 197

    31.2%

    按JCI指標(biāo)學(xué)科分區(qū) 收錄子集 分區(qū) 排名 百分位
    學(xué)科:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE SCIE Q4 152 / 198

    23.48%

    JCR分區(qū)的優(yōu)勢(shì)在于它可以幫助讀者對(duì)學(xué)術(shù)文獻(xiàn)質(zhì)量進(jìn)行評(píng)估。不同學(xué)科的文章引用量可能存在較大的差異,此時(shí)單獨(dú)依靠影響因子(IF)評(píng)價(jià)期刊的質(zhì)量可能是存在一定問題的。因此,JCR將期刊按照學(xué)科門類和影響因子分為不同的分區(qū),這樣讀者可以根據(jù)自己的研究領(lǐng)域和需求選擇合適的期刊。

    歷年影響因子趨勢(shì)圖

    發(fā)文數(shù)據(jù)

    2023-2024 年國(guó)家/地區(qū)發(fā)文量統(tǒng)計(jì)
    • 國(guó)家/地區(qū)數(shù)量
    • India27
    • CHINA MAINLAND23
    • USA16
    • England12
    • GERMANY (FED REP GER)12
    • Turkey11
    • Spain9
    • France8
    • Italy8
    • Portugal8

    投稿常見問題

    通訊方式:WILEY, 111 RIVER ST, HOBOKEN, USA, NJ, 07030-5774。

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