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To address the multi-classification problems of hyperspectral dataset, a new method with weighted kernel function based on Chernoff distance is proposed. Chernoff distance utilizes the information between categories and strengthens the separability of original dataset. The adjustable parameter in Chernoff distance can fit the hyperspectral dataset well compared with other least upper bounds. Pairwise...
Many rail accidents were caused by rail defects, therefore the detection of the rail defects is of vital importance. Using simulated and experimental measurements, the rail defect detection was carried out. The feature parameters were extracted both from time domain and time-frequency domain. Then the sequential backward selection method was applied to select the important feature parameters. After...
Based on the framework of support vector machines (SVM) using one against one (OAO) strategy, a new kernel method based on Bhattacharyya distance is proposed to raise the classification accuracy by combining the characteristics of hyperspectral data. The proposed method takes advantage of the non-uniform information distribution of hyperspectral data and makes the band with greater separability play...
Protein remote homology detection and fold recognition are central problems in bioinformatics. In this paper, two kinds of profile-level building blocks of protein sequences, binary profiles and N-nary profiles, are presented, which contain the evolutionary information of the protein sequence frequency profile. The two building blocks are applied for protein remote homology and fold detection tasks...
Support vector machine (SVM) appears to be a robust alternative for pattern recognition with hyperspectral data. However, this kernel-based method does not take into consideration the bio-physical meaning of the spectral signatures. Observation of real-life spectral signatures from the AVIRIS hyperspectral dataset shows that the useful information for classification is not equally distributed across...
Support vector machines (SVMs) have been engaged on image interpolation tasks recently. These methods employed only local pixel coordinates or neighbor pixels gray values as input properties and obtained poor quality result images. A novel SVMs interpolation scheme was proposed with increasing the local spatial properties as SVMs input information. At first a proper neighbor pixels model was selected...
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