EurekAlert!

Energy learning hyper-heuristic algorithm for cooperative task assignment of heterogeneous UAVs under complex constraints

The study addresses heterogeneous UAV cooperative task assignment under complex constraints via an energy learning ...
Occupational Health & Safety

Rethinking OEHS Training: Moving Beyond Compliance to Reduce Risk

Research shows that compliance-focused safety training alone rarely delivers lasting risk reduction, prompting calls for ...
EurekAlert!

A graph reinforcement learning framework for real-time distributed multi-robot task allocation

Effective task allocation has become a critical challenge for multi-robot systems operating in dynamic environments like search and rescue. Traditional methods, often based on static data and ...
Fox News

Doctors on key US health task force accused of prioritizing DEI over evidence-based medicine

An "independent" advisory panel of non-federal experts determining which preventative healthcare services insurers must cover is accused of being staffed with doctors who have shown a propensity to ...
VentureBeat

This new framework lets LLM agents learn from experience, no fine-tuning required

A new learning paradigm developed by University College London (UCL) and Huawei Noah’s Ark Lab enables large language model (LLM) agents to dynamically adapt to their environment without fine-tuning ...
IEEE

Collaborative Multitask Learning Framework Based on Constrained Bi-Level Gradient Optimization for Mechanical Fault Diagnosis

Abstract: In recent years, multitask learning (MTL) has attracted the increasing focus in the field of mechanical fault diagnosis. Relevant research shows that the MTL-based fault diagnosis frameworks ...
IEEE

Enhancing Task-Incremental Learning via a Prompt-Based Hybrid Convolutional Neural Networks (CNNs)-Vision Transformer (ViT) Framework

Abstract: Artificial neural network (ANN) models are widely used in various fields such as image classification, multi-object detection, intent prediction, military applications, and natural language ...
Frontiers

BrainTumNet: multi-task deep learning framework for brain tumor segmentation and classification using adaptive masked transformers

Background and objective: Accurate diagnosis of brain tumors significantly impacts patient prognosis and treatment planning. Traditional diagnostic methods primarily rely on clinicians’ subjective ...