机构

• 长春光学精密机械与物... [7]
• 自动化研究所 [3]
• 心理研究所 [2]
• 物理研究所 [1]
• 金属研究所 [1]
• 新疆天文台 [1]
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采集方式

• OAI收割 [16]

内容类型

• 会议论文 [10]
• 期刊论文 [6]

发表日期

• 2025 [1]
• 2019 [3]
• 2014 [1]
• 2012 [4]
• 2011 [3]
• 2009 [1]
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学科主题

• Gesture Re... [1]
• 工业与组织心理学 [1]

筛选

浏览/检索结果: 共16条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序作者升序作者降序 Assessment of LiDAR-Based Atmospheric Observations Using YOLOv9 for Sky Image Recognition 期刊论文  OAI收割 IEEE SENSORS JOURNAL, 2025, 卷号: 25, 期号: 1, 页码: 1825-1838 作者:  Xu, Long;  Lin, Xin;  Liu, Linmei;  Wang, Jiqin;  Lin, Xingkui   |  收藏  |  浏览/下载：4/0  |  提交时间：2025/02/27 Atmospheric modeling  Laser radar  Clouds  Accuracy  Meteorology  Data models  Atmospheric measurements  Stars  Predictive models  Image recognition  Atmospheric detection  data quality assessment  environmental monitoring  image recognition  LiDAR  YOLOv9   Low-cost biometric recognition system based on NIR palm vein image 期刊论文  OAI收割 IET BIOMETRICS, 2019, 卷号: 8, 期号: 3, 页码: 206-214 作者:  Wu, Wei;  Elliott, Stephen John;  Lin, Sen;  Yuan, Weiqi   |  收藏  |  浏览/下载：24/0  |  提交时间：2021/02/02 feature extraction  biometrics (access control)  vein recognition  image recognition  low-cost biometric recognition system  NIR palm vein image  high security  liveness detection  palm vein capture devices  practical palm vein recognition system  authors  (NIR) palm vein image  complementary metal-oxide-semiconductor camera  NIR charge-coupled device camera  discriminate palm vein features  recognition accuracy  1500 palm vein images  capture device   Low-cost biometric recognition system based on NIR palm vein image 期刊论文  OAI收割 IET BIOMETRICS, 2019, 卷号: 8, 期号: 3, 页码: 206-214 作者:  Lin S(林森);  Yuan, Weiqi;  Elliott, Stephen John;  Wu W(吴微)   |  收藏  |  浏览/下载：23/0  |  提交时间：2019/05/12 feature extraction  biometrics (access control)  vein recognition  image recognition  low-cost biometric recognition system  NIR palm vein image  high security  liveness detection  palm vein capture devices  practical palm vein recognition system  authors  (NIR) palm vein image  complementary metal-oxide-semiconductor camera  NIR charge-coupled device camera  discriminate palm vein features  recognition accuracy  1500 palm vein images  capture device   Research on Dynamic and Static Fusion Polymorphic Gesture Recognition Algorithm for Interactive Teaching Interface 会议论文  OAI收割 Beijing, China, November 29, 2018 - December 1, 2018 作者:  Feng, Zhiquan   |  收藏  |  浏览/下载：60/0  |  提交时间：2019/11/08 Application effect - Gesture recognition algorithm - People identification - Recognition accuracy - Reduction algorithms - Teaching equipments - Teaching interfaces - Training data sets   Semi-supervised Learning for RGB-D Object Recognition 会议论文  OAI收割 Stockholm, Sweden, 2014-08-01 作者:  Yanhua Cheng;  Xin Zhao;  Kaiqi Huang;  Tieniu Tan   |  收藏  |  浏览/下载：16/0  |  提交时间：2016/12/30 Accuracy    cameras    feature Extraction    object Recognition   Enhancing Cross-View Object Classification by Feature-Based Transfer Learning 会议论文  OAI收割 Tsukuba, Japan, 11-15 November 2012 作者:  Yi Mo;  Zhaoxiang Zhang;  Yunhong Wang   |  收藏  |  浏览/下载：13/0  |  提交时间：2017/02/09 Accuracy  Vectors  Training  Surveillance  Joints  Manuals  Pattern Recognition   Handwritten Chinese Text Recognition by Integrating Multiple Contexts 期刊论文  OAI收割 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2012, 卷号: 34, 期号: 8, 页码: 1469-1481 作者:  Wang, Qiu-Feng;  Yin, Fei;  Liu, Cheng-Lin 收藏  |  浏览/下载：42/0  |  提交时间：2015/08/12 Handwritten Chinese text recognition  confidence transformation  geometric models  language models  refined beam search  candidate character augmentation  maximum character accuracy training   On hyperspectral remotely sensed image classification based on MNF and AdaBoosting (EI CONFERENCE) 会议论文  OAI收割 2012 3rd IEEE/IET International Conference on Audio, Language and Image Processing, ICALIP 2012, July 16, 2012 - July 18, 2012, Shanghai, China 作者:  Yu P.;  Yu P.;  Gao X. 收藏  |  浏览/下载：28/0  |  提交时间：2013/03/25 As an effective statistical learning tool  AdaBoosting has been widely used in the field of pattern recognition. In this paper  a new method is proposed to improve the classification performance of hyperspectral images by combining the minimum noise fraction (MNF) and AdaBoosting. Because the hyperspectral imagery has many bands which have strong correlation and high redundancy  the hyperspectral data are pre-processed by the minimum noise fraction to reduce the data's dimensionality  whilst to remove noise bands simultaneously. Then  we use an AdaBoost algorithm to conduct the classification of hyperspectral remotely sensed image. Experimental results show that the classification accuracy is improved and the time of calculation is reduced as well. 2012 IEEE.   An approach to the misleading action solving in plan recognition (EI CONFERENCE) 会议论文  OAI收割 2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012, July 15, 2012 - July 17, 2012, Xian, Shaanxi, China 作者:  Wang Y.;  Wang Y.;  Wang Y.;  Wang Y.;  Wang Y. 收藏  |  浏览/下载：20/0  |  提交时间：2013/03/25 Misleading actions have not been considered in previous researches on plan recognition. It leads to poor recognition results for some special domains. This paper introduces new concepts including reliability  correlativity  and correlated action sequence etc. A novel algorithm is proposed to recognize a misleading action by using correlated action sequences. The proposed algorithm is shown to improve the accuracy of plan recognition. Moreover  it could also be applied to intrusion detection and network security problems. 2012 IEEE.   Efficient human action recognition using accumulated motion image and support vector machines (EI CONFERENCE) 会议论文  OAI收割 International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2011, November 19, 2011 - November 23, 2011, Suzhou, China 作者:  Zhang X.;  Zhang J.;  Zhang J.;  Zhang X.;  Zhang X. 收藏  |  浏览/下载：70/0  |  提交时间：2013/03/25 Vision-based human action recognition provides an advanced interface  and research in this field of human action recognition has been actively carried out. This paper describes a scheme for recognizing human actions from a video sequences. The proposed method is an extension of the Motion History Image(MHI) method based on the ordinal measure of accumulated motion  which is robust to variations of appearances. We define the accumulated motion image(AMI) using image differences firstly. Then the AMI of the video sequencesis resized to a MN regulation following the standard of training phases. Finally  we employ Support Vector Machine(SVM) as a classifier to distinguish the current activity in target video sequences. In a word  our proposed algorithm not only outperforms the state of art on public available KTH data set and Weizmann data set  but also proves practical to some real world applications  in addition  this method is computationally simple and able to achieve a satisfactory accuracy.