亚洲国产成人久久77-亚洲国产成人久久99精品-亚洲国产成人久久精品hezyo-亚洲国产成人久久精品动漫-人妖hd-人妖ts在线,一本道高清DVD在线视频,2020亚洲永久精品导航,国产久久视频在线视频观看

當(dāng)前位置: 首頁 JCRQ1 期刊介紹(非官網(wǎng))
Machine Intelligence Research

Machine Intelligence ResearchSCIE

國際簡(jiǎn)稱:MACH INTELL RES  參考譯名:機(jī)器智能研究

  • 中科院分區(qū)

    4區(qū)

  • CiteScore分區(qū)

    Q1

  • JCR分區(qū)

    Q1

基本信息:
ISSN:2731-538X
E-ISSN:2731-5398
是否OA:未開放
是否預(yù)警:否
TOP期刊:否
出版信息:
出版商:Chinese Academy of Sciences
出版語言:English
研究方向:Multiple
評(píng)價(jià)信息:
影響因子:6.4
CiteScore指數(shù):6.7
SJR指數(shù):1.68
SNIP指數(shù):2.72
發(fā)文數(shù)據(jù):
Gold OA文章占比:37.08%
研究類文章占比:89.09%
年發(fā)文量:55
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Machine Intelligence Research期刊介紹

Machine Intelligence Research, as an academic journal dedicated to promoting the development of the field of machine intelligence, reflects a positive response to national strategic needs and an open attitude towards global academic perspectives. This journal not only provides a platform for domestic and foreign researchers to showcase the latest research results, but also promotes academic exchanges and technological progress in key fields such as machine learning, deep learning, natural language processing, and computer vision by publishing high-quality original papers, reviews, and comments.

The publication content of the journal not only covers the basic theories of machine intelligence, but also pays special attention to cutting-edge innovations in this field, such as intelligent algorithms, big data processing, machine perception and cognition, etc. Through in-depth exploration of these contents, the journal aims to provide theoretical support and practical guidance for the technological progress of artificial intelligence, while also providing decision-making references and research perspectives for policy makers, industry experts, and academic researchers.

期刊簡(jiǎn)介Machine Intelligence Research期刊介紹

《Machine Intelligence Research》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)Machine Intelligence Research Cite Score數(shù)據(jù)

  • CiteScore:6.7
  • SJR:1.681
  • SNIP:2.721
學(xué)科類別 分區(qū) 排名 百分位
大類:Mathematics 小類:Applied Mathematics Q1 54 / 635

91%

大類:Mathematics 小類:Modeling and Simulation Q1 42 / 324

87%

大類:Mathematics 小類:Control and Systems Engineering Q1 78 / 321

75%

大類:Mathematics 小類:Computer Networks and Communications Q1 99 / 395

75%

大類:Mathematics 小類:Computer Science Applications Q2 211 / 817

74%

大類:Mathematics 小類:Signal Processing Q2 35 / 131

73%

大類:Mathematics 小類:Computer Vision and Pattern Recognition Q2 29 / 106

73%

大類:Mathematics 小類:Artificial Intelligence Q2 115 / 350

67%

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)Machine Intelligence Research 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) AUTOMATION & CONTROL SYSTEMS 自動(dòng)化與控制系統(tǒng) COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 計(jì)算機(jī):人工智能 4區(qū) 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)國際、國內(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)國際學(xué)術(shù)期刊影響力的參考數(shù)據(jù),得到了全國各地高校、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)Machine Intelligence Research 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:AUTOMATION & CONTROL SYSTEMS ESCI Q1 10 / 84

88.7%

學(xué)科:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE ESCI Q1 34 / 197

83%

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:AUTOMATION & CONTROL SYSTEMS ESCI Q1 12 / 84

86.31%

學(xué)科:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE ESCI Q1 36 / 198

82.07%

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

本刊中國學(xué)者近年發(fā)表論文

  • 1、YuNet: A Tiny Millisecond-level Face Detector

    Author: Wu, Wei; Peng, Hanyang; Yu, Shiqi

    Journal: MACHINE INTELLIGENCE RESEARCH. 2023; Vol. , Issue , pp. -. DOI: 10.1007/s11633-023-1423-y

  • 2、Deep Learning-based Moving Object Segmentation: Recent Progress and Research Prospects

    Author: Jiang, Rui; Zhu, Ruixiang; Su, Hu; Li, Yinlin; Xie, Yuan; Zou, Wei

    Journal: MACHINE INTELLIGENCE RESEARCH. 2023; Vol. , Issue , pp. -. DOI: 10.1007/s11633-022-1378-4

  • 3、AI in Human-computer Gaming: Techniques, Challenges and Opportunities

    Author: Yin, Qi-Yue; Yang, Jun; Huang, Kai-Qi; Zhao, Mei-Jing; Ni, Wan-Cheng; Liang, Bin; Huang, Yan; Wu, Shu; Wang, Liang

    Journal: MACHINE INTELLIGENCE RESEARCH. 2023; Vol. , Issue , pp. -. DOI: 10.1007/s11633-022-1384-6

  • 4、A Survey on Recent Advances and Challenges in Reinforcement Learning Methods for Task-oriented Dialogue Policy Learning

    Author: Kwan, Wai-Chung; Wang, Hong-Ru; Wang, Hui-Min; Wong, Kam-Fai

    Journal: MACHINE INTELLIGENCE RESEARCH. 2023; Vol. , Issue , pp. -. DOI: 10.1007/s11633-022-1347-y

  • 5、Dynamic Movement Primitives Based Robot Skills Learning

    Author: Kong, Ling-Huan; He, Wei; Chen, Wen-Shi; Zhang, Hui; Wang, Yao-Nan

    Journal: MACHINE INTELLIGENCE RESEARCH. 2023; Vol. , Issue , pp. -. DOI: 10.1007/s11633-022-1346-z

  • 6、DynamicRetriever: A Pre-trained Model-based IR System Without an Explicit Index

    Author: Zhou, Yu-Jia; Yao, Jing; Dou, Zhi-Cheng; Wu, Ledell; Wen, Ji-Rong

    Journal: MACHINE INTELLIGENCE RESEARCH. 2023; Vol. , Issue , pp. -. DOI: 10.1007/s11633-022-1373-9

  • 7、ECG Biometrics via Enhanced Correlation and Semantic-rich Embedding

    Author: Wang, Kui-Kui; Yang, Gong-Ping; Yang, Lu; Huang, Yu-Wen; Yin, Yi-Long

    Journal: MACHINE INTELLIGENCE RESEARCH. 2023; Vol. , Issue , pp. -. DOI: 10.1007/s11633-022-1345-0

  • 8、Dual-domain and Multiscale Fusion Deep Neural Network for PPG Biometric Recognition

    Author: Liu, Chun-Ying; Yang, Gong-Ping; Huang, Yu-Wen; Huang, Fu-Xian

    Journal: MACHINE INTELLIGENCE RESEARCH. 2023; Vol. , Issue , pp. -. DOI: 10.1007/s11633-022-1366-8

投稿常見問題