Results 161 to 170 of about 5,846,406 (312)

Automated Hand Flexor Tendon–Thickness Measurement in Systemic Sclerosis

open access: yesArthritis 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

Co-teaching: Robust training of deep neural networks with extremely noisy labels [PDF]

open access: yes, 2018
© 2018 Curran Associates Inc.All rights reserved. Deep learning with noisy labels is practically challenging, as the capacity of deep models is so high that they can totally memorize these noisy labels sooner or later during training. Nonetheless, recent
Tsang, IW   +7 more
core  

Incidence, Risk Factors and Management of Adverse Events in Contemporary Real‐World Care of Children with Juvenile Idiopathic Arthritis

open access: yesArthritis Care &Research, Accepted Article.
Objective We describe the frequency, risk factors, severity, and management of actionable and serious adverse events (AAE and SAE) in children with newly diagnosed Juvenile Idiopathic Arthritis (JIA) in Canada. Methods We enrolled patients within 3 months of JIA diagnosis in the Canadian Alliance of Pediatric Rheumatology Investigators (CAPRI) Registry,
Bashayer Alnuaimi   +10 more
wiley   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

open access: yesInternational Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam   +2 more
wiley   +1 more source

ADVANCED NEURAL NETWORKS AND DEEP LEARNING TECHNIQUES IN FINANCIAL MARKET PREDICTION [PDF]

open access: yesAnalele Universităţii Constantin Brâncuşi din Târgu Jiu : Seria Economie
This study investigates the role of artificial neural networks (ANN) and deep learning (DL) in the financial sector, focusing on their theoretical applications.
ENE CEZAR CATALIN
doaj  

A representer theorem for deep neural networks

open access: yesJ. Mach. Learn. Res., 2018
We propose to optimize the activation functions of a deep neural network by adding a corresponding functional regularization to the cost function. We justify the use of a second-order total-variation criterion. This allows us to derive a general representer theorem for deep neural networks that makes a direct connection with splines and sparsity ...
openaire   +5 more sources

Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane   +3 more
wiley   +1 more source

Speech Activity Detection in Online Broadcast Transcription Using Deep Neural Networks and Weighted Finite State Transducers

open access: yes, 2017
In this paper, a new approach to online Speech Activity Detection (SAD) is proposed. This approach is designed for the use in a system that carries out 24/7 transcription of radio/TV broadcasts containing a large amount of non-speech segments, such as ...
Matějů Lukáš   +3 more
core   +1 more source

Alzheimer's Disease Beyond Amyloid: Lessons From Atherosclerosis

open access: yes
Annals of Clinical and Translational Neurology, EarlyView.
Marcello Ciaccio, Luisa Agnello
wiley   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

open access: yesInternational 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

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