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Face recognition methods utilizing Sparse Representation based Classification (SRC) and Collaborative Representation based Classification (CRC) have recently attracted a great deal of attention due to inherent simplicity and efficiency. In this paper, we introduce the Large Margin Nearest Neighbor (LMNN), which learns a Mahalanobis distance metric that is applied, to SRC and CRC as the locality constraint...
There has been a defining problem of early warning threshold in power project investment, the accuracy and timeliness of early warning also can not be guaranteed. This paper is based on the optimal segmentation theory, combined with the actual situation of power project investment, splits historical engineering data optimally so as to determine the better segment number and give the early warning...
Self-healing is an interesting topic in SON (Self- Organizing Networks). In this paper, we investigate cell outage detection problem, and propose an improved TCM (Transductive confidence machines) based automatic cell outage detection algorithm. By incorporating a hypothesis test with the Neyman-Pearson criterion to improve the detection accuracy, the improved TCM can effectively detect cell outage...
In this paper, we are mostly interested in investigating how the study and discovery of the human visual cortex could be utilised to improve the computational models for visual recognition by computer vision. Many of the brain perceptual abilities in vision have corresponding algorithms exist in computer vision, and in this paper we discuss three such models. First we present a model that has the...
Eigenspace projection methods are widely used for feature extraction from hyperspectral images (HSI) for the classification of land cover. Projection transformation is used to reduce higher dimensional feature vectors to lower dimensional vectors for more accurate classification of land cover types. In this paper, a nearest feature line embedding (NFLE) transformation is proposed for the dimension...
Automatic TV commercial detection has become an indispensable part of content-based video analysis technique due to the explosive growth in TV commercial volume. In this paper, a multi-modal (i.e. visual, audio and textual modalities) commercial digesting scheme is proposed to alleviate two challenges in commercial detection, which are the generation of mid-level semantic descriptor and the application...
The probabilistic neural network (PNN) model plays a very important role for ship detection in synthetic aperture radar (SAR) imagery, however there are still some detection parameter need to improve for the requirement of detection accuracy and speed. This paper presents a new method based on combinatorial PNN model for ship detection in SAR imagery. The method includes 8-bit and 16-bit image processing...
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