Feature Based Representation for Coronary Segments
Conceptual Representation in Bilinguals: A Feature-Based Approach
... monolinguals, whereas when the task was in in Japanese, bilinguals verified pairs with Canadian-specific features more often compared to Japanese monolinguals. In contrast, the bilinguals’ verification rates for pairs ...
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Fingerprint Smear Detection Based on Subband Feature Representation
... subbands 4 ∼ 19; M(m 1 , . . . , m 16 ) denotes 16 mean values of SWT coefficients from subbands 4 ∼ 19; G(g 1 , . . . , g 27 ) stands for 27 additional feature parameters derived from GLCM. 2.3. DCT-Based ...
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Action localization in video using a graph-based feature representation
... First, we propose a new directed video graph suited for the localisation task. In the graph, the node describes a can- didate action region and its connectivity (edge) describes the similarity with the adjacent region ...
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Texture Feature Representation and Retrieval
... Texture has been extensively studied and used in literature since it plays a very important role in human visual perception. Texture refers to the spatial distribution of grey-level in an image. Micro textures refer to ...
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SigSpace – Class-Based Feature Representation for Scalable and Distributed Machine Learning
... blob or a corner. SIFT extracts blob like feature points and describe them with a scale, illumination, and rotational invariant descriptor. Unlike other histogram descriptors, SIFT algorithm does not give an ...
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Statistical Normalisation of Phase-based Feature Representation For Robust Speech Recognition
... proposed representation by evaluating statistical properties at vari- ous points along the parametrisation ...magnitude- based features into the phase domain. Based on the statistical struc- ture of ...
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Modular Feature Models: Representation and Configuration
... collaborative feature model design and ...as feature models become larger and more complicated, modular feature models tend to stabilize the feature model configuration execution ...new ...
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Feature Extraction and Representation for Face Recognition
... global representation as opposed to a bag-of-features approach should be ...the feature description is specifically adapted for the purpose of face ...a representation based on gradient ...
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Nested Graph Representation for Visual SLAM based on Local and Global Feature Processing
... 3. FEATURE EXTRACTION AND CLASSIFICATION Features extraction is the process of finding some sort of description that can be used later to identify the region or the object of interest and to differ this object ...
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Unsupervised Multi-Label Image and Texture Segmentation based on Optimal Feature Representation
... Segmentation based on Optimal Feature Representation Mehmet Cem CATALBAS Abstract: In this paper, an adaptive and robust unsupervised texture segmentation algorithm is ...successful ...
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A nonparametric feature for neonatal EEG seizure detection based on a representation of pseudo-periodicity
... Fourier- based methods to compactly represent such signals as they tend to spread the power of these signals over the range of the frequency variation in the ...accurate representation and detection of ...
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PanPhon: A Resource for Mapping IPA Segments to Articulatory Feature Vectors
... [email protected], [email protected], [email protected], [email protected], [email protected], [email protected] Abstract This paper contributes to a growing body of evidence that—when coupled with appropriate ...
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Feature trajectory dynamic time warping for clustering of speech segments
... (SADD). Since the phonetic alignment is provided in the former and the word alignments in the latter, the ground truth is available. Hence, we can use the external met- rics to quantify the quality of the resulting ...
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Superpixel based feature specific sparse representation for spectral-spatial classification of hyperspectral images
... c=1,...,C || Y − D c ∗ A ˆ c || 2 (5) Although the JSRC has a better classification accuracy than the SRC, it has several drawbacks: first, with the fixed (size and shape) window strategy, many unrelated pixels may be ...
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Feature Extraction and Classification from Boundary Representation
... particular feature types from the relational boundary model called the gener- alised edge–face graph ( GEFG ) ...is based on decomposition of GEFG into bicon- nected and triconnected subgraphs, and it effi- ...
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Feature Reduction and Representation Learning for Visual Applications
... general feature descriptor for both RGB and depth data and LFF in the RGB-D concatenation scheme reaches the highest accuracy in the experiment of feature ...continuous feature outperforms other ...
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Feature Extraction and Representation for Human Action Recognition
... the feature space) alignment, discriminative locality alignment unifies spectral analysis-based dimensionality reduction ...patches based on the alignment trick ...built based on each ...
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Face recognition via edge based Gabor feature representation for plastic surgery altered images
... efficient feature descriptors for recognizing surgically altered face ...face representation approach is aimed at mitigating the intra-subject varia- tions induced by plastic surgery ...
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Functional measurements based on feature tracking of cine magnetic resonance images identify left ventricular segments with myocardial scar
... right coronary artery (RCA), all others in the ...circumflex coronary artery (LCX) system in 6 ...other coronary arteries in 7 of the 17 scar patients and in two of the 13 non-scar ...to ...
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Effective Feature Representation for Clinical Text Concept Extraction
... of feature representation: dense repre- sentations that can be trained on any large text corpus (not necessarily using clinical text) and sparse, high-dimensional feature representations based ...
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