Search results for: Kaiping Wei
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BMC Bioinformatics > 2018 > 19 > 20 > 37-48
Background The traditional methods of visualizing high-dimensional data objects in low-dimensional metric spaces are subject to the basic limitations of metric space. These limitations result in multidimensional scaling that fails to faithfully represent non-metric similarity data. Results Multiple maps t-SNE (mm-tSNE) has drawn much attention due to the construction of multiple mappings in low-dimensional...
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Describing images in semantic terms is an important and challenging problem in content-based image retrieval. According to the strong relationship between colors and human emotions, an emotional image classification model based on color semantic terms is proposed in this paper. First, combined with PSO, fuzzy c-means clustering is implemented for color segmentation, and eight color clusters can be...
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2010 2nd International Conference on Future Computer and Communication > 1 > V1-796 - V1-801
As the computer technology developed nowadays, image retrieval is developing fast. Due to the semantic disparity between low-level feature and high-level feature of an image. We propose a novel algorithm called a kind of feedback image retrieval algorithm based on PSO, Wavelet and sub-block sorting thought (RPWA) in the paper. Firstly, we preprocess the sample images and abstract the color histogram...
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Image retrieval is a hot technology in the field of computer technology nowdays. This paper presents a novel image retrieval algorithm which is mainly used to solve problems for image retrieval in large image database. Firstly, preprocess the sample images, abstract the color histogram information of the partial image block and then calculate the sum of information. Extract several images and calculate...
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Virtual Instruction has triggered profound changes in the field of distance education. However, ldquoteachersrdquo usually ignore the emotional factors of students in VI environment, which will severely harm the quality of learning. Affective Intervention Learning Algorithm (AILA), a novel method for emotional interaction learning in virtual instruction is proposed in the paper, which tracks the affective...
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With an expert system, a novel fuzzy c-means clustering method based on PSO and expert system (PSFCM-ES) is proposed in this paper. The algorithm is formulated by incorporating the spatial neighborhood information into the standard FCM clustering algorithm. The k-nearest neighbor (k-NN) algorithm is introduced for calculating the weight in the spatially weighted FCM algorithm so as to improve the...
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Aiming at resolving the issue of Sand and Dust Storm (SDS) location in a remote sensing image, a new method is proposed in this paper to detect the center and intensity of a SDS automatically. First, SDS coverage area is extracted from remote sensing images by 2D-Otsu algorithm combined with fuzzy entropy, and the PSO algorithm is implemented to accelerate the process of global threshold selection...
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A novel approach is proposed to extract textual information for classification and recognition of ancient coins, which is based on tree-structured wavelet transform (TWT) and ant colony optimization (ACO) algorithm. Traditional methods of textural extraction focus on information only in low frequency channels. In this paper, in order to obtain texture information in all channels, incomplete TWT is...
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In order to effectively reduce the dependence on the experimental environment and make the teaching process more interesting, a method of virtual interactive experiment based on data glove is proposed in this paper. First, on the basis of analysis the structure of human hand, a virtual hand model with the joints as nodes is created. Then the definition of motion is discussed and a mapping between...
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This paper proposes an effective threshold selection method of image segmentation based on particle swarm optimization (PSO), which is embedded into two-dimensional Otsu algorithm. Traditional image segmentation methods are time-consuming computation and become an obstacle in real time application systems. In this paper, the threshold selection approach based on PSO is proposed to deal with threshold...
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This paper proposes an effective threshold selection method of image segmentation based on particle swarm optimization (PSO), which is embedded into two-dimensional Otsu algorithm. Traditional image segmentation methods are time??consuming computation and become an obstacle in real time application systems. In this paper, the threshold selection approach based on PSO is proposed to deal with threshold...
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A novel method for CT image segmentation of brain is proposed in this paper, with which, several regions that are suspicious of having pathological changes can be segmented rapidly and effectively. To avoid the affection of extra-cranial highlight pixels in the later processing, row scanning approach is introduced firstly to search for the boundary of the skull. Secondly, combined with morphological...
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An adaptive dissipative particle swarm with mutation operation (ADPSO) is presented that combines the idea of the particle swarm optimization with concepts of mutation from evolutionary algorithm. In this paper, the problem and improved of the dissipative particle swarm optimization are analyzed deeply. The improvement ADPSO adopts Cauchy mutation operation to escape from the attraction of local minimum...
