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This paper presents a genetic algorithm and back propagation neural network (GA-BP-NN) outburst prediction model with a structure of 6 × 13 × 1 according to basic theory of coal and gas outburst hazard classification prediction of coal mine and genetic algorithm, back propagation and neural network. Particularly, we also construct an application of outburst prediction of coal mine. From the learning...
Nearest Neighbor Classifier is one of the most classical lazy learning schemes. The basic nearest neighbor classifiers suffer from the common problem that the instances used to train the classifier are all stored indiscriminately, and as a result, the required memory storage is huge and response time becomes slow with a large database. In this paper, a new Instances Selection algorithm based on Classification...
MCS (minimal consistent set) is one of the classical algorithms for minimal consistent subset selection problem. However, when noisy samples are present classification accuracy can suffer. In addition, noise affect the size of minimal consistent set. Therefore, removing noise is an important issue before sample selection. In this paper, an improvement approach based on MCS to select the representative...
Detection of object of a known class is a fundamental problem of computer vision. The appearance of objects can change greatly due to illumination, view point, and articulation. For object classes with large intra-class variation, some divide-and-conquer strategy is necessary. Tree structured classifier models have been used for multi-view multi- pose object detection in previous work. This paper...
This paper proposes an approach to simultaneously detect and segment objects of a known category. Edgelet features are used to capture the local shape of the objects. For each feature a pair of base classifiers for detection and segmentation is built. The base segmentor is designed to predict the per-pixel figure-ground assignment around a neighborhood of the edgelet based on the feature response...
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