high-dimensional image space
Learning and Mapping Energy Functions of High-Dimensional Image Data
... parameter space (T, α) can be mapped using AD, and the results are similar to the phase space of the magnetized Ising function, as described in Section ...a high value of α, and attempted 20 AD ...
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Study of the Gap Discharge Phenomenon Based on Three-Dimensional Fractal
... of high voltage ...different high voltage to the needle-plate electrode under other conditions unchanged, carries out many experiments, and collects five groups of discharging channel plans of needle-plate ...
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Hashing Based Query Image Search using ORB Algorithm
... Query image search based on visual similarities has been lively topic of research in recent ...scalable image search. Usually hashing methods are used to embed high dimensional image ...
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SALIENT AREA DISCERNMENT VIA HIGH DIMENSIONAL COLOR TRANSFORM AND LOCAL SPECIAL PLATFORM
... like image segmentation, adaptive compression, and object ...background image elements. To detect salient regions in an image in terms of the saliency ...in high-dimensional color ...
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A new approach for data visualization problem
... original high dimensional space, we may be more capable of finding the possible relationship among the data points in the low dimensional space, ...recognition, image processing, ...
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Hubs in Space: Popular Nearest Neighbors in High-Dimensional Data
... Besides application areas that involve audio and image data (Aucouturier and Pachet, 2007; Doddington et al., 1998; Berenzweig, 2007; Hicklin et al., 2005), identifying hubness within data and methods from other ...
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To Show the Multiple Alignment of the Image search Hash Efficiency
... embedding high-dimensional feature descriptors into a similarity- preserving Hamming space with a low ...the high-dimensional feature ...
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Object Classification and Detection in High Dimensional Feature Space
... an image, predicting each time a discriminative score related to the presence or absence of the object to ...the image, placing each filter at an optimal image ...
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Improved Clustering Approach for high Dimensional Citrus Image data
... In this paper we consider the use of the mutual information (MI for short) to evaluate the “information content” of each individual feature with regard to the output class. The approximated evaluation of the mutual ...
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Study of Informative Value of Features in Rail Condition Monitoring
... data space to a high dimensional feature space using a Gaussian ...feature space we look for the smallest sphere that encloses the image of the ...data space, where it ...
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A Literature Survey on Query Adaptive Image Search using Hash Code
... Query image search based on visual similarities has been lively topic of research in recent ...scalable image search. Usually hashing methods are used to embed high dimensional image ...
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A Generalized Language Model in Tensor Space
... Tensor Space Language Model (TSLM), by utiliz- ing tensor networks and tensor ...a high-dimensional semantic space constructed by the tensor product of word ...this high-order tensor ...
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An Efficient Image Classification Using Class Imbalance In High-Dimensional Data
... In this paper, the SVM and class imbalance techniques was motivated by our interest in image mining, and the need for the methods, which can accomplish this task based on relational input data. This paper has ...
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NEW GENERATION OF COMPUTER AIDED DESIGN IN SPACE PLANNING METHODS A SURVEY AND A PROPOSAL
... CAD, space- planning allocation methods, which have been discussed and developed vigorously during the 1970s, became less so after ...that. Space planning is a critical issue during the architectural design ...
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Parameter variations in prediction skill optimization at ECMWF
... The evolution of the four parameter values in the 177 con- secutive ensembles is given in Fig. 1. A vertical column of markers represents parameter values of one ensemble. Dark markers correspond to parameter values with ...
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Dynamic Feature Induction: The Last Gist to the State of the Art
... low dimensional features together. Our algorithm does not join a high dimensional feature with either a low dimensional feature or another high dimensional ...feature ...
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Polynomial Kernel Function based Support Vectors for Data Stream Clustering
... of high dimensional ...a high dimensional characteristic space, in which support-vectors are describe a arbitrary shape training ...n-dimensional space a definitive set of ...
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Parallelization of Support Vector Machines
... data space to a high dimensional feature space using a Gaussian ...data space, where it forms a set of contours that enclose the data points and can be interpreted as cluster ...
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OFF LINE SIGNATURE VERIFICATION SYSTEM BASED ON DWT AND COMMON FEATURES EXTRACTION
... ) dimensional covariance ...1024 dimensional. In the 1024 dimensional space of unitary space, select the 900 dimensional feature component with the least corresponding value as ...
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Feature optimization in high dimensional chemical space: statistical and data mining solutions
... Structure and ligand-based virtual screening methods are widely employed in drug discovery process [1–4]. These methods are high dimensional and complex to analyze which pose some basic challenges. As the ...
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