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Recent work in terrain recognition for outdoor mobile robots mainly focused on several typical pure terrain sample classification, and only one terrain feature is extracted for terrain sample description. In this paper, a segmentation scheme for complex terrain samples is designed for the terrain recognition process. The segmentation scheme is achieved using the graph segmentation followed by the...
A robust appearance model is usually required in visual tracking, which can handle pose variation, illumination variation, occlusion and many other interferences occurring in video. So far, a number of tracking algorithms make use of image samples in previous frames to update appearance models. There are many limitations of that approach: 1) At the beginning of tracking, there exists no sufficient...
KPCA algorithm can solve the problem of nonlinear characteristic that the PCA algorithm can't handle with and the traditional curvelet decomposition algorithm cannot take full advantage of the fine scale component information. So we put forward KPCA algorithm and data fusion algorithm. The KPCA algorithm has a good effect on extracting face contour and the curve detail information through internal...
Extreme Learning Machine (ELM) for Single-hidden Layer Feedforward Neural Network (SLFN) has been attracting attentions because of its faster learning speed and better generalization performance than those of the traditional gradient-based learning algorithms. However, it has been proven that generalization performance of ELM classifier depends critically on the number of hidden neurons and the random...
Neural network has been widely used for nonlinear mapping, time-series estimation and classification. The unscented Kalman filter is a nonlinear parameter estimation algorithm. By means of it, weights update can be realized. In this paper a three layers neural network is used as a classification of the acupuncture EEG signals. The classifier directly classed the EEG instead of the feature values of...
Transductive confidence machines (TCMs) when used in classification problems can provide us with reliability for every classification. Many machine learning algorithms, such as KNN algorithm, etc., have been incorporated with TCM, while there's no SOM classification method based on TCM. Considering properties of SOM map unit, this paper first designs a novel nonconformity measurement and TCM-SOM classification...
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