Researchers have demonstrated a new technique that allows "self-driving laboratories" to collect at least 10 times more data ...

In joint research with the University of Tokyo (UTokyo), the National Institute of Advanced Industrial Science and Technology ...

Innovations in assistive AI and, ultimately, increased autonomy with agentic AI will redefine what engineers can achieve ...

The machine learning model outperformed the nomogram in terms of precision and specificity, highlighting its potential superiority in risk prediction. The SHapley additive explanations analysis ...

Real-time vehicle data are collected using cameras deployed along highways, and key traffic parameters such as flow, density, and speed are precisely extracted using the YOLOv8 object detection model.

Typical Azure Machine Learning Project Lifecycle (source: Microsoft). At the upcoming Visual Studio Live! @ Microsoft HQ 2025 conference in Redmond, Eric D. Boyd, founder and CEO of responsiveX, will ...

Sticking to an exercise routine is a challenge many people face. But a research team is using machine learning to uncover what keeps individuals committed to their workouts.

This paper addresses these challenges by proposing a novel Deep Learning (DL) approach for traffic prediction in V2X environments. We employ Bidirectional Long Short-Term Memory (BiLSTM) networks and ...

Electric vehicles are potential for electrifying traffic due to their effectiveness, environmental friendliness, and cleanliness Not only do electric cars (EVs) provide substantial loads for the ...

Elevate your traffic flow analysis with AI algorithms. Discover strategies for enhanced predictive accuracy using machine learning and neural networks.