[PDF] Top 20 An EM based multiple instance learning method for image classification
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An EM based multiple instance learning method for image classification
... propose an EM based learning algorithm to provide a comprehensive procedure for maximizing the measurement of diverse density on given multiple ...new EM based ... See full document
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A Dynamic Subspace Method for Hyperspectral Image Classification
... Subspace Method for Hyperspectral Image Classification Jinn-Min Yang, Bor-Chen Kuo, Pao-Ta Yu, Member, IEEE, and Chun-Hsiang Chuang Abstract—Many studies have demonstrated that multiple ... See full document
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A New Weighting Scheme with Multiple Classifiers Fusion for Image Classification
... statistical classification methods are not appropriate in classification of multisource data, since in most cases they cannot be modeled by a convenient multivariate statistical model ...from ... See full document
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Multiple Kernel Learning for Dimensionality Reduction
... of learning a unified space of low dimension for data in multiple feature ...knowledge for effectively analyzing a given data set, including choosing a proper set of visual features to better ... See full document
14
An Adaptive Learning Method for Target Tracking across Multiple Cameras
... 3 for all of the automatically learning methods mentioned ...learnt. For example, it is difficult to discover whether a blind region between cameras is closed or open, but this knowledge would help ... See full document
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SLEX-NWFE feature extraction method for hyperspectral image classification
... high dimensional vectors. NWFE is a very robust and superior feature extraction method in this aspect of view of image pixel. On the other hand, since adjacent bands in a pixel are usually highly ... See full document
2
An Effective Tuning Method for Cysteine State Classification
... state classification, we propose a 2-stage prediction ...SVM classification include the local profile PSSM, order of cysteines with the normalized protein length, physiochemical properties and structure ... See full document
12
A novel fuzzy C-means method for hyperspectral image classification
... and Image Processing - 723 Computer Software, Data Handling and Applications - 721 Computer Circuits and Logic Elements - 716 Telecommunication; Radar, Radio and Television ... See full document
2
An Efficient Image Authentication Method Based on Hamming Code
... According to our experimental results, our new hybrid method can effectively eliminate burst bit errors, and our recovered pixels in detail areas can actually gain very high clarity.. [r] ... See full document
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An integrated method in wavelet-based image compression
... The dtfjerentialpulse code modulation is used to reduce the entropy of the lowest frequency subimage of the discrete wavelet transform and to achieve high compres[r] ... See full document
16
An Optimal Classification Method for Biological and Medical Data
... induce classification rules. The first method is the decision tree-based method, which has been developed in the last few decades ...of an induction motor 18 to classify normal or ... See full document
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An improved presentation method for relevance feedback in a content-based image retrieval system
... 5. Conclusions In this paper, we proposed an improved presentation method for relevance feedback in a CBIR system. The as- sumption is that a good presentation of the query results can guide the user ... See full document
4
An efficient method for creating benchmark classifications for automatic workpiece classification systems
... The value of the membership function obtained by aggregating the data for all subjects' comparisons of a pair of workpieces is still a fuzzy number, and it is dif[r] ... See full document
14
Eigenregions for image classification
... Eigenregions are geometrical features Eigenregions are geometrical features encompass area, location and shape. encompass area, location and shape[r] ... See full document
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Using Modified Bagging and Boosting Algorithms in Multiple Classifiers System for Remote Sensing Image Classification
... They are briefly outlined below. 2.2. The Bagging Algorithm The Bagging algorithm works with a training sample of fixed size. The samples are resampled according to a given probability distribution. The error is ... See full document
16
Computer-based rating method for evaluating multiple visual stimuli on multiple scales
... rating method (focus-on-stimulus) are proposed for rating multiple visual stimuli with respect to multiple ...paper-and-pencil method as the basis for comparison, the performance ... See full document
18
Hyperspectral Image Classification Using Dynamic Classifier Selection with Multiple Feature Extractions
... in multiple classifier system ...procedures for mitigate Hughes phenomenon in hyperspectral image ...extractions for improving classification ...strategy based on local ... See full document
5
Reinforcement learning for an ART-based fuzzy adaptive learning control network
... IEEE TRANSACTIONS ON NEURAL. 3, MAY 1996 reinforcement signals from the critic network, which has only one output node since it is used to predict the external scalar reinforcem[r] ... See full document
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A repetitive learning method based on sliding mode for robot control
... through learning. Hence, this sliding mode based repetitive learning controller outperforms the sliding mode ...every learning period, since the learning gains can not be infinitely ... See full document
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An Image Retrieval Method Based on Color-Complexity and Spatial-Histogram Features
... in an image to record the distribution of the pixels' colors that are present in different spatial positions within an ...other image feature proposed in this paper is the color-complexity ... See full document
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