Results 61 to 70 of about 134,020 (300)
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
Arthritis Care &Research, Accepted Article.Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein +3 more
wiley +1 more source
Neural Networks and Deep Learning [PDF]
Neural networks and deep learning have significantly advanced the field of artificial intelligence, offering solutions to complex problems such as image recognition, natural language processing, and decision-making tasks.
Riya Anjali Bansal, Aryan Ramesh Pillai
core +1 more source
Arthritis Care &Research, EarlyView.Interstitial lung disease (ILD) is a significant cause of morbidity and mortality in patients with inflammatory rheumatic disorders (IRDs). High‐resolution computed tomography (HRCT) is widely considered the gold standard for the noninvasive assessment of ILD; however, its interpretation is constrained by substantial interobserver variability and the ...
Alexander Pfeil +7 more
wiley +1 more source
Recognition of radio signals with deep learning Neural Networks
, 2016 Nowadays, the use of Artificial Neural Networks shows continuity in many different applications. In particular, the use of deep learning type neural networks, seen as impractical previously, is increasing by processing power growth.
ARTUNER, HARUN +3 more
core +1 more source
Artificial neural networks and deep learning [PDF]
, 2018 The purpose of this paper is to study the principles of neural networks working and deep learning, to analyze their structure and learn the details of mechanisms these systems ...
Konopelko, A. I.
core +1 more source
Automated Hand Flexor Tendon–Thickness Measurement in Systemic Sclerosis
Arthritis Care &Research, EarlyView.Objective Systemic sclerosis (SSc) can affect flexor tendons, contributing to hand function problems and reduced quality of life. Tendon changes are currently assessed with ultrasonography and measured manually, a time‐consuming process prone to interobserver variability.
Mark Greveling +4 more
wiley +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.More than 10 000 metal‐coated silicon MEMS cantilevers are fabricated and characterized to build a large‐scale experimental dataset spanning multiple vibrational modes. Machine learning algorithms are benchmarked to predict resonance frequency and quality factor, with ensemble based models achieving accuracy approaching experimental uncertainty.
Sina Zare Pakzad +8 more
wiley +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