Spiking neural networks for computer vision [PDF]
Interface Focus, 2018 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.
Michael Hopkins +3 more
semanticscholar +6 more sources
Computer Simulation of Neural Networks Using Spreadsheets: The Dawn of the Age of Camelot [PDF]
Освітній вимір, 2018 Semerikov S.O., Teplytsʹkyy I.O., Yechkalo YU.V. and Kiv A.E. Computer Simulation of Neural Networks Using Spreadsheets: The Dawn of the Age of Camelot.
Сергій Семеріков +3 more
doaj +2 more sources
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
doaj +1 more source
Run, Don't Walk: Chasing Higher FLOPS for Faster Neural Networks [PDF]
Computer Vision and Pattern Recognition, 2023 To design fast neural networks, many works have been focusing on reducing the number of floating-point operations (FLOPs). We observe that such reduction in FLOPs, however, does not necessarily lead to a similar level of re-duction in latency.
Jierun Chen +6 more
semanticscholar +1 more source
Federated Reservoir Computing Neural Networks [PDF]
2021 International Joint Conference on Neural Networks (IJCNN), 2021 A critical aspect in Federated Learning is the aggregation strategy for the combination of multiple models, trained on the edge, into a single model that incorporates all the knowledge in the federation. Common Federated Learning approaches for Recurrent Neural Networks (RNNs) do not provide guarantees on the predictive performance of the aggregated ...
Bacciu D. +4 more
openaire +2 more sources
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
doaj +1 more source
Plenoxels: Radiance Fields without Neural Networks [PDF]
Computer Vision and Pattern Recognition, 2021 We introduce Plenoxels (plenoptic voxels), a systemfor photorealistic view synthesis. Plenoxels represent a scene as a sparse 3D grid with spherical harmonics.
Alex Yu +5 more
semanticscholar +1 more source
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
doaj +1 more source
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning [PDF]
IEEE Transactions on Medical Imaging, 2016 Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets and deep convolutional neural networks (CNNs).
Hoo-Chang Shin +8 more
semanticscholar +1 more source
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
doaj +1 more source