Results 51 to 60 of about 422,144 (319)
A Biologically Plausible Learning Rule for Deep Learning in the Brain [PDF]
, 2018 Researchers have proposed that deep learning, which is providing important progress in a wide range of high complexity tasks, might inspire new insights into learning in the brain. However, the methods used for deep learning by artificial neural networks
Bohté, Sander +2 more
core +2 more sources
Arthritis Care &Research, EarlyView.Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos +2 more
wiley +1 more source
Burst Pressure Prediction of API 5L X-Grade Dented Pipelines Using Deep Neural Network
Journal of Marine Science and Engineering, 2020 Mechanical damage is recognized as a problem that reduces the performance of oil and gas pipelines and has been the subject of continuous research. The artificial neural network in the spotlight recently is expected to be another solution to solve the ...
Dohan Oh +3 more
doaj +1 more source
Using Explainable AI to Measure Feature Contribution to Uncertainty
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022 The application of artificial intelligence techniques in safety-critical domains such as medicine and self-driving vehicles has raised questions regarding its trustworthiness and reliability.
Katherine Elizabeth Brown +1 more
doaj +1 more source
Detecting Adversarial Examples through Nonlinear Dimensionality Reduction [PDF]
, 2019 Deep neural networks are vulnerable to adversarial examples, i.e., carefully-perturbed inputs aimed to mislead classification. This work proposes a detection method based on combining non-linear dimensionality reduction and density estimation techniques.
Bacciu, Davide +2 more
core +1 more source
Advanced Engineering Materials, EarlyView.Additive manufacturing provides precise control over the placement of continuous fibres within polymer matrices, enabling customised mechanical performance in composite components. This article explores processing strategies, mechanical testing, and modelling approaches for additive manufactured continuous fibre‐reinforced composites.
Cherian Thomas, Amir Hosein Sakhaei
wiley +1 more source
A Review of Optical Neural Networks
Applied Sciences, 2022 With the continuous miniaturization of conventional integrated circuits, obstacles such as excessive cost, increased resistance to electronic motion, and increased energy consumption are gradually slowing down the development of electrical computing and ...
Danni Zhang, Zhongwei Tan
doaj +1 more source
Identifying Quantum Phase Transitions using Artificial Neural Networks on Experimental Data
, 2018 Machine learning techniques such as artificial neural networks are currently revolutionizing many technological areas and have also proven successful in quantum physics applications.
Asteria, Luca +7 more
core +1 more source
Advanced Functional Materials, EarlyView.An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone +11 more
wiley +1 more source
Fault diagnosis of high-speed train wheelset bearing based on a lightweight neural network
工程科学学报, 2021 Deep learning is gaining attention in the field of mechanical equipment fault diagnosis. With the help of deep learning techniques, deep neural networks (DNNs) have great potential for machinery fault diagnosis.
Fei-yue DENG +4 more
doaj +1 more source