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科研机构
兰州理工大学 [3]
自动化研究所 [1]
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期刊论文 [4]
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2015 [2]
2014 [2]
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Image classification framework based on topics learning of multiple features
期刊论文
Journal of Computational Information Systems, 2015, 卷号: 11, 期号: 13, 页码: 4811-4819
作者:
Cao, Jie
;
Wu, Yakun
;
Li, Xiaoxu
收藏
  |  
浏览/下载:13/0
  |  
提交时间:2020/11/14
Classification (of information)
Semantics
Classification framework
Classification performance
Image features
Multiple features
Multiple features fusions
Real data sets
Semantic features
Topic Modeling
Multi-focus image fusion based on sparse feature matrix decomposition and morphological filtering
期刊论文
OPTICS COMMUNICATIONS, 2015, 卷号: 342, 页码: 1-11
作者:
Li, Hui
;
Li, Li
;
Zhang, Jixiang
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  |  
浏览/下载:23/0
  |  
提交时间:2016/03/30
Sparse matrix decomposition
Multi-focus image fusion
Feature extraction
Morphological filtering
Target robust tracking in clutter environment with non-Gaussian related noise
期刊论文
Guangdianzi Jiguang/Journal of Optoelectronics Laser, 2014, 卷号: 25, 期号: 12, 页码: 2393-2399
作者:
Sun, Tao
;
Cao, Jie
;
Li, Wei
;
Li, Jun
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  |  
浏览/下载:2/0
  |  
提交时间:2020/11/14
Clutter (information theory)
Distribution functions
Functions
Gaussian distribution
Monte Carlo methods
Target tracking
Tracking (position)
Vehicles
Cauchy-Gaussian mixtures
Correlative noise
Mathematical expressions
Multiple features fusions
Nonlinear system modeling
Object Tracking
Particle filter
Proposal distribution
An improved UPF object tracking algorithm based on multi-feature fusion
期刊论文
Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University, 2014, 卷号: 48, 期号: 10, 页码: 1473-1478
作者:
Li, Xiao-Xu
;
Dai, Bin
;
Cao, Jie
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  |  
浏览/下载:26/0
  |  
提交时间:2020/11/14
Image processing
Kalman filters
Textures
Uncertainty analysis
Iterated Kalman filter
Multiple features fusions
Object Tracking
Uncertainty measurements
Unscented particle filters
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