Machine learning algorithm fully reconstructs LHC particle collisions

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...
UC San Diego Today

Safer Railroads Through Ultrasound

Existing defect detection tools using ultrasound rely on phased array ultrasound. In this method, many transducers are pointed in the same direction to generate an image of that specific area. This ...
Frontiers

Smart Additive Manufacturing of Advanced Materials Using Artificial Intelligence and Machine Learning

The field of additive manufacturing is undergoing a profound transformation as artificial intelligence (AI) and machine learning (ML) become integral to the ...
IEEE

Defect Detection and Correction in OpenMP: A Static Analysis and Machine Learning-Based Solution

Abstract: Concurrency defects such as race conditions, deadlocks, and improper synchronization remain a critical challenge in developing reliable OpenMP-based parallel applications. Traditional static ...
Semiconductor Engineering

Catching Critical Defects In TSVs And Stacked Chips

The small and complicated features of TSVs give rise to different defect types. Defects can form during any of the TSV ...
GitHub

Steel Defect Detection with YOLOv8

The dataset is already organized in YOLO format in the steel_dataset/ directory. If you need to reorganize from original format, see utility/reorganize_dataset.py. steel-defect-detection/ ├── ...
Que.com on MSN

AI transforms rocket parts manufacturing at the European Space Agency

The European Space Agency (ESA) is accelerating a quiet revolution on the factory floor: using artificial intelligence to ...
IEEE

A Comprehensive Investigation into Strip Steel Defect Detection using Traditional Machine Learning and Deep Learning Models

Abstract: The steel manufacturing sector places great importance on guaranteeing the quality of strip steel products, which has led to a thorough investigation of defect detection approaches. This ...