Results 81 to 90 of about 3,537 (211)

Late Positive Potentials as an Index of “Desirably Difficult” Learning Processes Engaged During Language Comprehension: ERP Evidence From Studies of Domain Knowledge

Psychophysiology, Volume 63, Issue 4, April 2026.
ABSTRACT Electrophysiological studies of language comprehension have primarily examined the kind of information that comes to mind, and when, as people process words and build message‐level understanding. However, less is known about the factors that allow people to commit the message‐level information to memory for future use.
Melissa Troyer, Marta Kutas, Kara D. Federmeier   +2 more
wiley   +1 more source

Attention-Guided Multi-Task Learning for Fault Detection, Classification, and Localization in Power Transmission Systems

Energies
Timely and accurate fault diagnosis in power transmission systems is critical to ensuring grid stability, operational safety, and minimal service disruption.
Md Samsul Alam, Md Raisul Islam, Rui Fan, Md Shafayat Alam Shazid, Abu Shouaib Hasan   +4 more
doaj   +1 more source

Cultivating Future Student Leaders: Core Self‐Evaluation and Student Leadership Practices With the Mediating Role of Motivation to Lead

Future in Educational Research, Volume 4, Issue 1, Page 42-55, March 2026.
ABSTRACT Quality leadership practices among university student leaders are imperative for ensuring proper discipline within universities and fostering the future career success of students. This study aims to explore the factors that influence leadership practices among university student leaders. Data were gathered through a multistage sampling method
Miaoling Zhang, Lei Mee Thien
wiley   +1 more source

Heterogeneous Multi-task Learning with Expert Diversity

, 2022
Predicting multiple heterogeneous biological and medical targets is a challenge for traditional deep learning models. In contrast to single-task learning, in which a separate model is trained for each target, multi-task learning (MTL) optimizes a single ...
Tung, Frederick, Aoki, Raquel, Oliveira, Gabriel L.   +2 more
core   +1 more source

3D imaging‐based AI models outperform demographic models and excel in tibial sizing compared with 2D models in total knee arthroplasty planning: A systematic review

Knee Surgery, Sports Traumatology, Arthroscopy, Volume 34, Issue 3, Page 1157-1169, March 2026.
Abstract Purpose Accurate preoperative implant sizing is a critical component of successful total knee arthroplasty (TKA). Artificial intelligence (AI) has emerged as a promising tool for enhancing preoperative planning. This is achieved through predictive modelling based on different input modalities, including computed tomography (CT), plain ...
Randa Elsheikh, Zainab Aqeel Khan, George Mihai Avram, Rolf Huegli, Andrej M. Nowakowski, Michael T. Hirschmann   +5 more
wiley   +1 more source

Joint Sparse and Low-Rank Multi-Task Learning with Extended Multi-Attribute Profile for Hyperspectral Target Detection

Remote Sensing, 2019
Target detection is an active area in hyperspectral imagery (HSI) processing. Many algorithms have been proposed for the past decades. However, the conventional detectors mainly benefit from the spectral information without fully exploiting the spatial ...
Xing Wu, Xia Zhang, Nan Wang, Yi Cen
doaj   +1 more source

Fruit freshness detection based on multi-task convolutional neural network

Current Research in Food Science
Background: Fruit freshness detection by computer vision is essential for many agricultural applications, e.g., automatic harvesting and supply chain monitoring.
Yinsheng Zhang, Xudong Yang, Yongbo Cheng, Xiaojun Wu, Xiulan Sun, Ruiqi Hou, Haiyan Wang   +6 more
doaj   +1 more source

DSPCI-MTL: Dynamic split point computing in multi-task learning implementation with collaborative intelligence

Alexandria Engineering Journal
Deep Neural Networks (DNNs) have become a crucial technology in image processing, renowned for their ability to generate effective feature maps. The integration of DNNs within Internet of Things (IoT) environments, particularly in multi-task robots and swarm systems, has positioned them as vital components in various applications.
M.Faruk Sahin, S. Faegheh Yeganli, Farzad Kiani   +2 more
openaire   +3 more sources

Task Uncertainty Loss Reduce Negative Transfer in Asymmetric Multi-task Feature Learning (Student Abstract)

, 2021
Multi-task learning (MTL) is frequently used in settings where a target task has to be learnt based on limited training data, but knowledge can be leveraged from related auxiliary tasks.
Nagarajan, Niranjan, Suphavilai, Chayaporn, Peres da Silva, Rafael   +2 more
core   +1 more source

MTL-AraBERT: An Enhanced Multi-Task Learning Model for Arabic Aspect-Based Sentiment Analysis

Computers
Aspect-based sentiment analysis (ABSA) is a fine-grained type of sentiment analysis; it works on an aspect level. It mainly focuses on extracting aspect terms from text or reviews, categorizing the aspect terms, and classifying the sentiment polarities toward each aspect term and aspect category.
Arwa Fadel, Mostafa Saleh, Reda Salama, Osama Abulnaja   +3 more
openaire   +2 more sources