Results 1 to 10 of about 170,112 (245)
Digital holographic microscopy applied to 3D computer microvision by using deep neural networks [PDF]
EPJ Web of Conferences, 2023 Deep neural networks are increasingly applied in many branches of applied science such as computer vision and image processing by increasing performances of instruments.
Brito Carcaño Jesús E. +6 more
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Building a decoder of perceptual decisions from microsaccades and pupil size
Frontiers in Psychology, 2022 Many studies have reported neural correlates of visual awareness across several brain regions, including the sensory, parietal, and frontal areas. In most of these studies, participants were instructed to explicitly report their perceptual experience ...
Ryohei Nakayama +8 more
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Correlation between neural responses and human perception in figure-ground segregation
Frontiers in Systems Neuroscience, 2023 Segmentation of a natural scene into objects (figures) and background (ground) is one of crucial functions for object recognition and scene understanding.
Motofumi Shishikura +3 more
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An overview of neural networks for medical image recognition [PDF]
E3S Web of Conferences, 2023 Medical image recognition plays a crucial role in computer diagnostics and has been greatly enhanced by the advancements in deep learning techniques, particularly neural networks.
Berezovsky V.V., Vygovskaya N.V.
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Enhanced gradient learning for deep neural networks
IET Image Processing, 2022 Deep neural networks have achieved great success in both computer vision and natural language processing tasks. How to improve the gradient flows is crucial in training very deep neural networks. To address this challenge, a gradient enhancement approach
Ming Yan +5 more
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Computational and topological properties of neural networks by means of graph-theoretic parameters
Alexandria Engineering Journal, 2023 A neural network is a computer system modeled on the nerve tissue and nervous system. In this sense, neural networks refer to systems of neurons, either organic or artificial in nature.
Asad Khan +5 more
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Journal of Imaging, 2023 Artificial neural networks can solve various tasks in computer vision, such as image classification, object detection, and general recognition.
Ladislav Karrach, Elena Pivarčiová
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AI-Track-tive: open-source software for automated recognition and counting of surface semi-tracks using computer vision (artificial intelligence) [PDF]
Geochronology, 2021 A new method for automatic counting of etched fission tracks in minerals is described and presented in this article. Artificial intelligence techniques such as deep neural networks and computer vision were trained to detect fission surface semi-tracks on
S. Nachtergaele, J. De Grave
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Quantum Neural Network for Quantum Neural Computing
Research, 2023 Neural networks have achieved impressive breakthroughs in both industry and academia. How to effectively develop neural networks on quantum computing devices is a challenging open problem. Here, we propose a new quantum neural network model for quantum neural computing using (classically controlled) single-qubit operations and measurements on real ...
Min-Gang Zhou +5 more
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Neural computing with coherent laser networks
Nanophotonics, 2023 AbstractWe show that coherent laser networks (CLNs) exhibit emergent neural computing capabilities. The proposed scheme is built on harnessing the collective behavior of laser networks for storing a number of phase patterns as stable fixed points of the governing dynamical equations and retrieving such patterns through proper excitation conditions ...
Mohammad-Ali Miri, Vinod Menon
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