Results 11 to 20 of about 160,762 (267)
CGENet: A Deep Graph Model for COVID-19 Detection Based on Chest CT
Biology, 2021 Accurate and timely diagnosis of COVID-19 is indispensable to control its spread. This study proposes a novel explainable COVID-19 diagnosis system called CGENet based on graph embedding and an extreme learning machine for chest CT images. We put forward
Si-Yuan Lu +3 more
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Color-based object recognition [PDF]
Pattern Recognition, 1997 Abstract The purpose is to arrive at recognition of multicolored objects invariant to a substantial change in viewpoint, object geometry and illumination. Assuming dichromatic reflectance and white illumination, it is shown that normalized color rgb, saturation S and hue H, and the newly proposed color models c 1 c 2 c 3 and
Gevers, Th., Smeulders, A.W.M.
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Spatiotemporal neural dynamics of object recognition under uncertainty in humans
eLife, 2023 While there is a wealth of knowledge about core object recognition—our ability to recognize clear, high-contrast object images—how the brain accomplishes object recognition tasks under increased uncertainty remains poorly understood.
Yuan-hao Wu, Ella Podvalny, Biyu J He
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Causal neural mechanisms of context-based object recognition
eLife, 2021 Objects can be recognized based on their intrinsic features, including shape, color, and texture. In daily life, however, such features are often not clearly visible, for example when objects appear in the periphery, in clutter, or at a distance ...
Miles Wischnewski, Marius V Peelen
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Nikol’skii–Type Inequalities for Trigonometric Polynomials for Lorentz–Zygmund Spaces
Journal of Function Spaces, 2020 Nikol’skii–type inequalities, that is inequalities between different metrics of trigonometric polynomials on the torus Td for the Lorentz–Zygmund spaces, are obtained. The results of previous paper “Nikol’skii inequalities for Lorentz–Zygmund spaces” are
Leo R. Ya. Doktorski
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On Image Ｒecognition Using Bidirectional Feature Pyramid and Deep Neural Network
Journal of Harbin University of Science and Technology, 2021 Object recognition is one of the fundamental tasks in the area of computer vision. The development of deep neural networks advances the object recognition. Nonetheless，multi-scale object recognition still remains to be a challenging task.
ZHAO Sheng, ZHAO Li
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Reiteration Formulae for the Real Interpolation Method Including L or R Limiting Spaces
Journal of Function Spaces, 2020 We consider a real interpolation method defined by means of slowly varying functions. We present some reiteration formulae including so-called L or R limiting interpolation spaces.
Leo R. Ya. Doktorski
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Object recognition methods based on RGB-D images
Xi'an Gongcheng Daxue xuebao, 2021 Object recognition is one of the main contents of machine vision research. RGB-D image, which integrates depth features, provides a new way for accuracy improving of object recognition.
Xun LI +5 more
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The Role of CaMKII Overexpression and Oxidation in Atrial Fibrillation—A Simulation Study
Frontiers in Physiology, 2020 This simulation study aims to investigate how the Calcium/calmodulin-dependent protein kinase II (CaMKII) overexpression and oxidation would influence the cardiac electrophysiological behavior and its arrhythmogenic mechanism in atria. A new-built CaMKII
Wei Wang +8 more
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Submodular Object Recognition [PDF]
2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014 We present a novel object recognition framework based on multiple figure-ground hypotheses with a large object spatial support, generated by bottom-up processes and mid-level cues in an unsupervised manner. We exploit the benefit of regression for discriminating segments' categories and qualities, where a regressor is trained to each category using the
Fan Zhu 0001 +2 more
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