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In this paper, we will propose a new approach about how to categorize viewfinder images captured by digital cameras. This new unsupervised learning approach based-on visual characters of the images and LDA (Latent Dirichlet Allocation) model. In this approach, we represent the image of a scene by a collection of local regions, denoted as codewords. The image codewords which include visual characters...
Feature selection is to select an informative subset from original feature set aiming at reducing the dimension of the feature space and enhancing the performance of the classifier. It is a crucial problem of pattern recognition and has attracted much attention in recent years. In this paper, we have proposed a multi-population univariate marginal distribution algorithm using random population to...
Feature selection is an effective data preprocessing step to reduce the dimension of feature space and save storage space. Binary particle swarm optimization (BPSO) has been applied successfully to solve feature selection problem. But it was easy to fall into local optimal point. M2BPSO was an improved BPSO algorithm. The particles of M2BPSO were updated by using various evolutionary strategies according...
The risk of common diseases is likely determined by single nucleotide polymorphisms (SNPs). However, due to the tremendous number of candidate SNPs, there is a clear need to genotyping by selecting only a subset of all SNPs that are highly associated with a specific disease. In this paper, a new algorithm which is based on a hybrid of binary Particle Swarm Optimization (BPSO) and estimation distribution...
With the rapid development of high-throughput genotyping technologies, more and more attentions are paid to the disease association study identifying DNA variations that are highly associated with a specific disease. One main challenge for this study is to find the optimal subsets of Single Nucleotide Polymorphisms (SNPs) which are most tightly associated with diseases. Feature selection which might...
With the rapid development of high-throughput genotyping technologies, more and more attentions are paid to the disease association study identifying DNA variations that are highly associated with a specific disease. One main challenge for this study is to find the optimal subsets of Single Nucleotide Polymorphisms (SNPs) which are most tightly associated with diseases. Feature selection has become...
Shenzhen located in South China has experienced a rapid period of construction land expansion over the past three decades. This paper focuses on the pattern change and the sprawl categories about the construction land integrating remote sensing and geographic information systems (GIS). We analyzed the spatial and temporal patterns of the construction land for the three counties in Shenzhen. The overlay...
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