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Image classification is an important problem in computer vision. All existing image classification approaches tend to classify images of distinctly different objects. In this paper, we attempt to classify two similar image classes, Chinese and European classical architecture. First, Gabor filter is utilized to catch texture features of images. Then color histogram distance is adopted as a coefficient...
In this paper, an improved support vector machines recursive feature elimination (SVM-RFE) approach for feature selection of hyperspectral data is proposed. An automatic model selection (AMS) algorithm using radius margin bound is integrated into the process of feature selection before feature ranking, and the ranking criterion used by standard SVM-RFE is replaced with a new criterion derived from...
In this paper, a multimodal image retrieval framework integrating the information in both audio and visual domain via Bayesian decision level fusion is proposed. In both domains, a statistical model for each semantic class is learned. Based on the Bayes' theorem, the a posteriori probability of each class given a query is calculated in the audio domain, which is propagated to the images classified...
In this paper we propose PHOTO (pyramid histogram of topics), a new representation for image classification. We partition the image into hierarchical cells and learn the topic histogram using pLSA over each cell with EM algorithm. Then we concatenate the topic histograms over the cells at all levels to form a ldquolongrdquo vector, i.e. pyramid histogram of topics. Finally AdaBoost classifiers are...
Feature recognition of multi-class imaginary movements is an important subject of brain-computer interface based on imaginary movement. In this paper, using the method of two-dimensional time-frequency analysis combined with Fisher separability analysis to study multi-channel synchronization, multi-class imaginary movements potential information of typical subjects. Also we have extracted the feature...
In architectural and mechanical engineering, man-made CAD models often have some prominent contours and regular shapes. These features are important to the visual perception. Traditional mesh simplification methods are not very suitable for this kind of models because in the simplified results some important mini structures and shape regularities are always missed. In this paper, we propose a new...
In this paper, we propose some technologies of multi-biometric feature identification, and present a framework of biometric identification system. The contributions of this paper include the following aspects: (1) the information of biological features are prevented from being forged or modified in network transmission by using a scrambling encryption algorithm of Semi-Fragile Watermarking(SFW) which...
A hybrid approach for the surface segmentation of sparse triangle meshes is presented. The algorithm realizes the segmentation of different regions of triangle meshes through twice segmentations phases: in the first phase, for sparse mesh regions, the edge-based method is used after combination of planes according to the variance of the dihedral angle of normal vector; in the second phase, for other...
We propose a new approach for recognizing object classes which is based on the intuitive idea that human beings are able to perform the task well given only thumbnails (coarse scale version) of images. Unlike previous work which uses local image features at fine scales, our approach uses thumbnails directly, and captures their high-order correlations at coarse scales through deep multi-layer neural...
Vehicle-based estimation system on large scale crop acreage, which was equipped with GPS receivers, GIS software and a video camera on a off-road vehicle, can capture the images of video and calculate the crop acreage proportion based on matching between GPS information and image recognition. The system provides the credible data for government to make decision and provides technological method. In...
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