Results 21 to 30 of about 9,277,012 (302)
From single neurons to behavior in the jellyfish Aurelia aurita
eLife, 2019 Jellyfish nerve nets provide insight into the origins of nervous systems, as both their taxonomic position and their evolutionary age imply that jellyfish resemble some of the earliest neuron-bearing, actively-swimming animals. Here, we develop the first
Fabian Pallasdies +3 more
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Impact of socioeconomic status on end-of-life costs: a systematic review and meta-analysis
BMC Palliative Care, 2020 Background Socioeconomic inequalities in access to, and utilization of medical care have been shown in many jurisdictions. However, the extent to which they exist at end-of-life (EOL) remains unclear. Methods Studies in MEDLINE, EMBASE, CINAHL, ProQuest,
Caberry W. Yu +2 more
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ACM SIGSPATIAL International Workshop on Advances in Geographic Information Systems, 2020 : An Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the biological nervous systems, such as the brain, which process information.
Satchidananda Dehuri +2 more
semanticscholar +1 more source
Deep Convolutional Neural Network for Inverse Problems in Imaging [PDF]
IEEE Transactions on Image Processing, 2016 In this paper, we propose a novel deep convolutional neural network (CNN)-based algorithm for solving ill-posed inverse problems. Regularized iterative algorithms have emerged as the standard approach to ill-posed inverse problems in the past few decades.
Kyong Hwan Jin +3 more
semanticscholar +1 more source
Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud [PDF]
Computer Vision and Pattern Recognition, 2020 In this paper, we propose a graph neural network to detect objects from a LiDAR point cloud. Towards this end, we encode the point cloud efficiently in a fixed radius near-neighbors graph. We design a graph neural network, named Point-GNN, to predict the
Weijing Shi, R. Rajkumar
semanticscholar +1 more source
Variable neural networks for adaptive control of nonlinear systems [PDF]
, 1999 This paper is concerned with the adaptive control of continuous-time nonlinear dynamical systems using neural networks. A novel neural network architecture, referred to as a variable neural network, is proposed and shown to be useful in approximating the
Billings, S.A. +2 more
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Neural Network Applications [PDF]
, 1995 Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in ...
Jain, L.C., Veelenturf, L.P.J., Vonk, E.
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A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures
Neural Computation, 2019 Recurrent neural networks (RNNs) have been widely adopted in research areas concerned with sequential data, such as text, audio, and video. However, RNNs consisting of sigma cells or tanh cells are unable to learn the relevant information of input data ...
Yong Yu +3 more
semanticscholar +1 more source
Design of a Configurable Spike-Encoding Circuit Based on Focal Plane Array
Applied Sciences, 2023 Spiking neural networks inspired by biological models are gaining popularity in artificial intelligence due to their ability to solve diverse problems while reducing energy consumption.
Di Lu +4 more
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Barren plateaus in quantum neural network training landscapes [PDF]
Nature Communications, 2018 Many experimental proposals for noisy intermediate scale quantum devices involve training a parameterized quantum circuit with a classical optimization loop.
J. McClean +4 more
semanticscholar +1 more source