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In clinical practice, the magnetic resonance imaging (MRI) is a prevalent neuroimaging technique for Alzheimer's disease (AD) diagnosis. As a learning using privileged information (LUPI) algorithm, SVM+ has shown its effectiveness on the classification of brain disorders, with single-modal neuroimaging samples for testing but multimodal neuroimaging samples for training. In this work, we propose to...
Glioma is one of the most common brain tumors with high mortality and its histological grading and typing is important both in therapeutic decision and prognosis evaluation. This paper aims at using the high-throughput image feature analysis method to estimate the histological grade and type of a patient by using Magnetic Resonance Imaging (MRI) instead of histological examination. The proposed method...
Traffic flow prediction has become a hot spot in the intelligent transportation system study. In this paper, novel methods are proposed to predict traffic flow. We divide 24 hours into 4 stages according to the bimodal distribution of traffic flow, and integrate topology features of urban traffic network into 4 typical machine learning methods. Experiments on the traffic flow of Qinhuangdao city demonstrate...
Shaft orbit plays an important role in condition monitoring and fault diagnosis for hydropower unit. A novel method of shaft orbit identification based on low-level image feature representation and classification is proposed. The main characteristic is that the vibrations of the shaft in terms of displacements are used to draw points in an image panel at a fixed scale, resulting in the shaft orbit...
Multi-person tracking and detection is widely used in human robot interaction, which has been a hot topic in computer vision. In this paper, we utilize a tracking-by-detection framework to track many persons at the same time. We use HOG and LBP features to describe person's characteristics in a scene and train a strong classifier using Adaboost algorithm. In the tracking part, we use a particle filter...
In this paper, a 7-DoF robot table tennis system is presented, which adopts a stereo vision system as its perceptional sensor and a humanoid robot arm as its manipulator. The batting policy, which can return various incoming balls to a desired location, is learned through empirical data based on e-support vector regression(e-SVR). Two experiments, playing with a launcher machine and rallying with...
A hierarchical feature fusion strategy based on Support Vector Machine (SVM) and Dempster-Shafer Evidence Theory is proposed for SAR image automatic target recognition in this paper. This strategy has three fusion hierarchies corresponding to three features. Principle Component Analysis (PCA), Local Discriminant Embedding (LDE) and Non-negative Matrix Factor (NMF) features are extracted from images...
Feature extraction is the key technology and the core task of Synthetic Aperture Radar (SAR) target recognition. In this paper, a new target feature extracting method based on Sparse Non-negative Matrix Factorization (SNMF) is presented, which mainly use SNMF as the method to decompose the SAR target image and to construct the sparse feature vector. By this means, the similarity inside each cluster...
To solve the problems of most communication signals modulation recognition methods' computational complexity and classifier training difficulties, a method of modulation recognition is proposed based on particle swarm optimization(PSO) and support vector machine (SVM). Combine wavelet decomposition theory with the modulated signals' instantaneous characteristics, high-order cumulants and fractal theory...
The rough entropy (RoughEn) is developed based on the rough set theory. It has the advantage of low computational complexity, because there is no parameter to set in RoughEn. In this paper, we characterized the feature of surface electromyography (SEMG) signal with RoughEn and then used support vector machine to classify six different hand motions. The sample entropy, wavelet entropy and approximate...
Feature selection is a key step in automatic text categorization system and it has a significant impact on classification result. In this paper we do research on mutual information (MI) which is one basic method of feature selection. Firstly, we found out three main problems of MI by analyzing the formula of MI theoretically and systematically the MI loss, the information difference among categories,...
Geomagnetic reference map is the basis for geomagnetic navigation, and modeling of regional geomagnetic field is one of the available methods to construct the geomagnetic reference map. Common-used modeling methods are not so fit for the small-scale regional geomagnetic field, so new ways to modeling of regional geomagnetic field is needed. The total intensity of geomagnetic field is a complicated...
Power transformer is one of the most expensive component of electrical power plants and the failures of such transformer can result in serious power system issues, so fault forecasting for power transformer is very important to insure the whole power system runs normally. In this paper, a novel fault prediction approach for power transformer based on Support Vector Machine (SVM) is presented using...
Active learning is a promising tool to improve the performance of content-based image retrieval (CBIR). As a commonly used active learning approach, angle-diversity provides the most informative images to user for feedback. However, it suffers from the problem that the query concept is diverse and the numbers of the positive and the negative images are imbalanced. As a consequence, the positive samples...
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