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期刊名字 | MACHINE VISION AND APPLICATIONS MACH VISION APPL LetPub评分 5.2
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声誉 6.3 影响力 3.8 速度 7.5 | |||||||||||||||||||||||||||||
期刊ISSN | 0932-8092 | 微信扫码收藏此期刊 | ||||||||||||||||||||||||||||
E-ISSN | 1432-1769 | |||||||||||||||||||||||||||||
2020-2021最新IF (数据来源于搜索引擎) | 登录后查看IF和趋势图 | |||||||||||||||||||||||||||||
2020-2021自引率 | 6.10%登录查看自引率趋势图 | |||||||||||||||||||||||||||||
h-index | 58 | |||||||||||||||||||||||||||||
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期刊简介 | Machine Vision and Applications publishes high-quality technical contributions in machine vision research and development. Specifically, the editors encourage submittals in all applications and engineering aspects of image-related computing. In particular, original contributions dealing with scientific, commercial, industrial, military, and biomedical applications of machine vision, are all within the scope of the journal. Particular emphasis is placed on engineering and technology aspects of image processing and computer vision. The following aspects of machine vision applications are of interest: algorithms, architectures, VLSI implementations, AI techniques and expert systems for machine vision, front-end sensing, multidimensional and multisensor machine vision, real-time techniques, image databases, virtual reality and visualization. Papers must include a significant experimental validation component. | |||||||||||||||||||||||||||||
期刊官方网站 | https://www.springer.com/138 | |||||||||||||||||||||||||||||
期刊投稿网址 | https://www.editorialmanager.com/mvap | |||||||||||||||||||||||||||||
作者指南网址 | https://www.springer.com/138/submission-guidelines | |||||||||||||||||||||||||||||
是否OA开放访问 | No | |||||||||||||||||||||||||||||
通讯方式 | SPRINGER, 233 SPRING ST, NEW YORK, USA, NY, 10013 | |||||||||||||||||||||||||||||
出版商 | Springer Berlin Heidelberg | |||||||||||||||||||||||||||||
涉及的研究方向 | 工程技术-工程:电子与电气 | |||||||||||||||||||||||||||||
出版国家或地区 | UNITED STATES | |||||||||||||||||||||||||||||
出版语言 | English | |||||||||||||||||||||||||||||
出版周期 | Bimonthly | |||||||||||||||||||||||||||||
出版年份 | 1988 | |||||||||||||||||||||||||||||
年文章数 | 87登录查看年文章数趋势图 | |||||||||||||||||||||||||||||
Gold OA文章占比 | 10.77% | |||||||||||||||||||||||||||||
研究类文章占比: 文章 ÷(文章 + 综述) | 100.00% | |||||||||||||||||||||||||||||
WOS期刊SCI分区 ( 2020-2021年最新版) | WOS分区等级:3区
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中科院《国际期刊预警 名单(试行)》名单 | 2021年12月发布的2021版:不在预警名单中 2021年01月发布的2020版:不在预警名单中 | |||||||||||||||||||||||||||||
中科院SCI期刊分区 ( 2021年12月最新基础版) | 登录查看中科院JCR分区趋势图
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中科院SCI期刊分区 ( 2021年12月最新升级版) |
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中科院SCI期刊分区 ( 2020年12月旧的升级版) |
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SCI期刊收录coverage | Science Citation Index Expanded (SCIE) Scopus (CiteScore) | |||||||||||||||||||||||||||||
PubMed Central (PMC)链接 | http://www.ncbi.nlm.nih.gov/nlmcatalog?term=0932-8092%5BISSN%5D | |||||||||||||||||||||||||||||
平均审稿速度 | 网友分享经验: 平均6.5个月 | |||||||||||||||||||||||||||||
平均录用比例 | 网友分享经验: 容易 | |||||||||||||||||||||||||||||
期刊常用信息链接 |
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登录查看自引率趋势图 |
登录查看中科院JCR分区趋势图 |
登录查看年文章数趋势图 |
中国学者近期发表的论文 | |
1. | Robust graticule intersection localization for rotated topographic maps Author: Luan Dong, Qin Yan, Fengling Zheng Journal: MACHINE VISION AND APPLICATIONS, 2019, Vol., , DOI:10.1007/s00138-019-01025-9 DOI |
2. | Topology-aware non-rigid point set registration via global–local topology preservation Author: Song Ge, Guoliang Fan Journal: MACHINE VISION AND APPLICATIONS, 2019, Vol., , DOI:10.1007/s00138-019-01024-w DOI |
3. | A novel method for breast mass segmentation: from superpixel to subpixel segmentation Author: Shenghua Gu, Yi Chen, Fangqing Sheng, Tianming Zhan, Yunjie Chen Journal: MACHINE VISION AND APPLICATIONS, 2019, Vol., , DOI:10.1007/s00138-019-01020-0 DOI |
4. | Soft decision optimization method for robust fundamental matrix estimation Author: Chun-Bao Xiao, Da-Zheng Feng, Ming-Dong Yuan Journal: MACHINE VISION AND APPLICATIONS, 2019, Vol., , DOI:10.1007/s00138-019-01019-7 DOI |
5. | Correction to: Retinal vessel extraction using dynamic multi-scale matched filtering and dynamic threshold processing based on histogram fitting Author: Duoduo Gou, Ying Wei, Hong Fu, Ning Yan Journal: MACHINE VISION AND APPLICATIONS, 2019, Vol., , DOI:10.1007/s00138-019-01018-8 DOI |
6. | Gait-based age progression/regression: a baseline and performance evaluation by age group classification and cross-age gait identification Author: Chi Xu, Yasushi Makihara, Yasushi Yagi, Jianfeng Lu Journal: MACHINE VISION AND APPLICATIONS, 2019, Vol., , DOI:10.1007/s00138-019-01015-x DOI |
7. | Camera pose estimation from lines: a fast, robust and general method Author: Ping Wang, Guili Xu, Yuehua Cheng, Qida Yu Journal: MACHINE VISION AND APPLICATIONS, 2019, Vol., , DOI:10.1007/s00138-019-01012-0 DOI |
8. | Collaborative tracking based on contextual information and local patches Author: Hua Bao, Yixiang Lu, Houde Dai, Mingqiang Lin Journal: MACHINE VISION AND APPLICATIONS, 2019, Vol., , DOI:10.1007/s00138-019-01011-1 DOI |
9. | Beyond feature integration: a coarse-to-fine framework for cascade correlation tracking Author: Dongdong Li, Gongjian Wen, Yangliu Kuai, Fatih Porikli Journal: MACHINE VISION AND APPLICATIONS, 2019, Vol., , DOI:10.1007/s00138-019-01009-9 DOI |
10. | Hard negative mining for correlation filters in visual tracking Author: Zhuojin Sun, Yong Wang, Robert Laganière Journal: MACHINE VISION AND APPLICATIONS, 2019, Vol., , DOI:10.1007/s00138-019-01004-0 DOI |
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