Results 11 to 20 of about 1,347,345 (241)
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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Superquadric-Based Object Recognition [PDF]
, 2001 This paper proposes a technique for object recognition using superquadric built models. Superquadrics, which are three dimensional models suitable for part-level representation of objects, are reconstructed from range images using the recover-and-select paradigm.
Krivic, Jaka, Solina, Franc
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Probabilistic Search for Object Segmentation and Recognition [PDF]
, 2002 The problem of searching for a model-based scene interpretation is analyzed within a probabilistic framework. Object models are formulated as generative models for range data of the scene. A new statistical criterion, the truncated object probability, is
D. G. Lowe +12 more
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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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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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Monocular SLAM Supported Object Recognition [PDF]
, 2015 In this work, we develop a monocular SLAM-aware object recognition system that is able to achieve considerably stronger recognition performance, as compared to classical object recognition systems that function on a frame-by-frame basis. By incorporating
Leonard, John, Pillai, Sudeep
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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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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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