Knowledge Graph, Large Language Model, BERT, Knowledge Management, Small and Medium-Sized Enterprises, Accounting, Supply Chain Management Zheng, Y. (2026) Knowledge Graph Application in KM for ...

To help professionals build these capabilities, we have curated a list of the best applied AI and data science courses.

A deep learning–based system for detecting employee drowsiness during virtual meetings using facial cues like yawning and eye closure. Built with ResNet50V2 and fine-tuned on diverse, augmented ...

Repository to track the progress in Meta-Learning (MtL), including the datasets and the current state-of-the-art for the most common MtL problems.

Abstract: Transfer learning in robotics aims to transfer knowledge across different robot agents or tasks. Current methods in trajectory tracking problems leverage ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

In large public multi-site fMRI datasets, the sample characteristics, data acquisition methods, and MRI scanner models vary across sites and datasets. This non-neural variability obscures neural ...

Introduction: Alzheimer’s disease (AD) is one of the most common neurodegenerative disabilities that often leads to memory loss, confusion, difficulty in language and trouble with motor coordination.

Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, Shanghai Frontiers Science Center of Molecule Intelligent Syntheses, School of Chemistry and Molecular ...