Results 11 to 20 of about 161,581 (266)
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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SatGeo-NeRF: Geometrically Regularized NeRF for Satellite Imagery [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information SciencesWe present SatGeo-NeRF, a geometrically regularized NeRF for satellite imagery that mitigates overfitting-induced geometric artifacts observed in current state-of-the-art models using three model-agnostic regularizers.
V. Wagner +3 more
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Object Recognition with and without Objects [PDF]
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017 While recent deep neural networks have achieved a promising performance on object recognition, they rely implicitly on the visual contents of the whole image. In this paper, we train deep neural networks on the foreground (object) and background (context) regions of images respectively.
Zhuotun Zhu, Lingxi Xie, Alan L. Yuille
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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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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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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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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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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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Operating System for Runtime Reconfigurable Multiprocessor Systems
International Journal of Reconfigurable Computing, 2011 Operating systems traditionally handle the task scheduling of one or more application instances on processor-like hardware architectures. RAMPSoC, a novel runtime adaptive multiprocessor System-on-Chip, exploits the dynamic reconfiguration on FPGAs to ...
Diana Göhringer +3 more
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