In this paper1, we propose an eLearning activity control model that is used to efficiently and graphically defining SCORM's content aggregation model and its sequencing prerequisites through a formal approach. In ...
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The practical teaching for the majors of rail transit in colleges and universities involves a large number of high-cost, high-consumption, large-scale or comprehensive training. It will often encounter high-risk or ex...
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In November of 2005 a measurement series was conducted on different kinds of reference objects to compare the results of the FRM-II (ANTARES) and the Budapest (Radiography Station) research reactor in the field of neu...
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ISBN:
(纸本)9781932078749
In November of 2005 a measurement series was conducted on different kinds of reference objects to compare the results of the FRM-II (ANTARES) and the Budapest (Radiography Station) research reactor in the field of neutron radiography, gamma radiography, classical tomography and discrete tomography by an ANDOR CCD camera and Imaging plate with BAS 2500 Scanner (contributed by AIDA software).
This paper proposes a method for robustly matching active appearance models (AAMs) on images with gross disturbances (outliers). The method consists of two steps. First, an initial residual is calculated by comparing ...
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ISBN:
(数字)9783540264316
ISBN:
(纸本)3540250522
This paper proposes a method for robustly matching active appearance models (AAMs) on images with gross disturbances (outliers). The method consists of two steps. First, an initial residual is calculated by comparing model and image appearance, and modes of the residual are analyzed. Second, all possible mode combinations are tested by evaluating an objective function. The objective function allows the selection of an outlier-free mode combination. Experiments demonstrate the ability of the robust matching method to successfully cope with outliers - compared to standard AAM matching, no degeneration of the model during matching occurs.
The landscape of natural language processing (NLP) has been revolutionized by advancements that enable the upstream training of knowledge-rich models for downstream tasks, particularly named entity recognition (NER). ...
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A novel optimal multilevel thresholding for histogram-based image segmentation is presented in this paper. It is based on the estimation of the statistical parameters of different classes under the assumption that the...
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A text line detection method based on wavelet transformation and mutation analysis is proposed in this paper. First the character density image is acquired from the input document image by the project function with st...
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In this paper, we apply a multiple regression method based on canonical correlation analysis (CCA) to face data modelling. CCA is a factor analysis method which exploits the correlation between two high dimensional si...
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In this paper, we apply a multiple regression method based on canonical correlation analysis (CCA) to face data modelling. CCA is a factor analysis method which exploits the correlation between two high dimensional signals. We first use CCA to perform 3D face reconstruction and in a separate application we predict near-infrared (NIR) face texture. In both cases, the input data are color (RGB) face images. Experiments show, that due to the correlation between input and output signal, only a small number of canonical factors are needed to describe the functional relation of RGB images to the respective output (NIR images and 3D depth maps) with reasonable accuracy
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