Results 91 to 100 of about 5,803,394 (295)

Smart Flexible Tactile Sensors: Recent Progress in Device Designs, Intelligent Algorithms, and Multidisciplinary Applications

Advanced Intelligent Discovery, EarlyView.
Flexible tactile sensors have considerable potential for broad application in healthcare monitoring, human–machine interfaces, and bioinspired robotics. This review explores recent progress in device design, performance optimization, and intelligent applications. It highlights how AI algorithms enhance environmental adaptability and perception accuracy
Siyuan Wang, Ming Dong, Rongrong Bao, Caofeng Pan   +3 more
wiley   +1 more source

Multitask Learning with Local Attention for Tibetan Speech Recognition

Complexity, 2020
In this paper, we propose to incorporate the local attention in WaveNet-CTC to improve the performance of Tibetan speech recognition in multitask learning.
Hui Wang, Fei Gao, Yue Zhao, Li Yang, Jianjian Yue, Huilin Ma   +5 more
doaj   +1 more source

FIRE‐GNN: Force‐Informed, Relaxed Equivariance Graph Neural Network for Rapid and Accurate Prediction of Surface Properties

Advanced Intelligent Discovery, EarlyView.
This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu, Claire Schlesinger, Karan Mudaliar, Jordan Leung, Robin Walters, Peter Schindler   +5 more
wiley   +1 more source

Federated foundation models for psychiatry: a new paradigm for diagnosis, prognosis, and treatment of mood disorders

Frontiers in Psychiatry
Multimodal Multitask Federated Foundation Models (M3T-FedFMs) represent a new frontier in artificial intelligence (AI), enabling integration of diverse data modalities and multitask learning while preserving data confidentiality through federated ...
Maryam Ebrahimi, Rajeev Sahay, Bita Akram, Bita Akram, Seyyedali Hosseinalipour, Seyyedali Hosseinalipour   +5 more
doaj   +1 more source

A Multimodal Intelligent System for Human Digital Twin Simulation with Continuous Kinematic Data Tracking, Biometric Prognosis, and Cognitive State Feedback in Industrial Environments

Advanced Intelligent Discovery, EarlyView.
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury, Sebastian Gratz‐Kelly, Eric Wagner, Paul Motzki, Martina Lehser   +4 more
wiley   +1 more source

Collaborative Estimation of Tropical Cyclone Wind Radii With Multitask Learning and Multiteacher Distillation

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Wind radii provide a quantitative measure of the structural characteristics of tropical cyclones (TCs), and accurate estimation of wind radii is crucial for disaster prevention and emergency response.
Jia Liu, Yinlei Yue, Yongjun Jin, Kaijun Ren, Xiang Wang, Kefeng Deng, Chongjiu Deng, Ke Deng   +7 more
doaj   +1 more source

Information Extraction from Electronic Medical Records Using Multitask Recurrent Neural Network with Contextual Word Embedding

Applied Sciences, 2019
Clinical named entity recognition is an essential task for humans to analyze large-scale electronic medical records efficiently. Traditional rule-based solutions need considerable human effort to build rules and dictionaries; machine learning-based ...
Jianliang Yang, Yuenan Liu, Minghui Qian, Chenghua Guan, Xiangfei Yuan   +4 more
doaj   +1 more source

Multitask Learning Strengthens Adversarial Robustness [PDF]

, 2020
Although deep networks achieve strong accuracy on a range of computer vision benchmarks, they remain vulnerable to adversarial attacks, where imperceptible input perturbations fool the network. We present both theoretical and empirical analyses that connect the adversarial robustness of a model to the number of tasks that it is trained on.
Mao, Chengzhi, Gupta, Amogh, Nitin, Vikram, Ray, Baishakhi, Song, Shuran, Yang, Junfeng, Vondrick, Carl   +6 more
openaire   +2 more sources

A Robust Deep Temporal Causal Discovery Platform for Single‐Cell Gene Regulatory Network Reconstruction

Advanced Intelligent Discovery, EarlyView.
scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta, Madison Dautle, Shaoqiang Zhang, Yong Chen   +3 more
wiley   +1 more source

AS‐pHopt: An Optimal pH Prediction Model Enhanced by Active Site of Enzymes

Advanced Intelligent Discovery, EarlyView.
To address the low accuracy of enzyme optimal pH (pHopt) prediction, this study develops active site‐based pHopt (AS‐pHopt), a prediction model enhanced by active site information and pseudo‐label prediction. Integrating key structural and physicochemical features affecting enzyme pHopt, AS‐pHopt uses Evolutionary Scale Modeling (ESM)‐2 with active ...
Wenxiang Song, Xinmin Li, Hongbo Yu, Le Xiong, Guixia Liu, Weihua Li, Yun Tang   +6 more
wiley   +1 more source