Results 1 to 10 of about 219,698 (314)
Spiking neural networks for computer vision [PDF]
Interface Focus, 2018 Abstract State-of-the-art computer vision systems use frame-based cameras that sample the visual scene as a series of high-resolution images. These are then processed using convolutional neural networks using neurons with continuous outputs.
Petrut Antoniu Bogdan +2 more
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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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Superconductor Computing for Neural Networks [PDF]
IEEE Micro, 2021 The superconductor single-flux-quantum (SFQ) logic family has been recognized as a promising solution for the post-Moore era, thanks to the ultrafast and low-power switching characteristics of superconductor devices. Researchers have made tremendous efforts in various aspects, especially in device and circuit design.
Koki Ishida +9 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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A New Method on Kerma Estimation in Mammography Screenings [PDF]
Journal of Biomedical Physics and Engineering, 2021 Background: Given the extensive use and preferred diagnostic method in common mammography tests for screening and diagnosis of breast cancer, there is concern about the increased dose absorbed by the patient due to the sensitivity of the breast tissue ...
Mohammad Nabipour +4 more
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