No Code Autonomous AI Research Assistant for Deep Web Research

Create a no-code AI researcher with two research modes and verifiable links, so you get quick answers and deeper findings ...
IEEE

Subarea Collaborative Deep Q-Network With Online Learning: Advanced Multi-Agent Routing Strategies for Dynamic Maritime Networks

Abstract: As the shipping industry evolves, communication-limited non-terrestrial networks (NTN) like maritime communication networks face increasing challenges, particularly due to frequent and large ...
GitHub

A comprehensive Python framework designed for exploring the loss landscapes of deep learning models.

Landscaper is available on PyPI, making it easy to install and integrate into your projects. @misc{https://doi.org/10.5281/zenodo.15874987, doi = {10.5281/ZENODO ...
eWeek

7 Robots Handling Jobs Too Dangerous for Humans

Meet seven robots already tackling bomb disposal, firefighting, deep-sea exploration, pipeline inspection, construction, ...
IEEE

A Novel Multi-scale Residual Active Deep Q-learning Network for Intelligent Bearing Fault Diagnosis with Small Training Data

Abstract: In bearing fault diagnosis (BFD), deep reinforcement learning (DRL) offers a promising solution by applying rewards to optimize fault decision-making strategies. However, the lack of ...
GitHub

EdgeTrain: Automated Resource Adjustment for Efficient Edge AI Training

EdgeTrain is a Python package designed to dynamically adjust deep learning training parameters and strategies based on CPU and GPU performance. It optimizes the training process by adjusting batch ...