First-ever black hole image sharpened using machine learning

The historic first image of the Messier 87 (M87) supermassive black hole, captured using the Event Horizon Telescope, has ...
Frontiers

Defect Diagnosis of Visible Light Images of Photovoltaic Modules Based on Active Transfer Learning

The final, formatted version of the article will be published soon. To address the challenges of missed detection and false detection of bird droppings and dust defects caused by data imbalance during ...
Frontiers

External defect detection of Orah mandarin based on a non-brightness correction algorithm

External defect detection is a crucial step in Orah mandarin citrus grading. However, in existing defect detection algorithms by image processing, Orah mandarin surfaces exhibit characteristics such ...
Scientific Research Publishing

Cheng, J.C.P. and Wang, M. (2018) Automated Detection of Sewer Pipe Defects in Closed-Circuit Television Images Using Deep Learning Techniques. Automation in Construction, 95 ...

ABSTRACT: Regular pipeline inspections are crucial for timely identification of critical defects and ensuring pipeline integrity. To address the challenges of detecting defects in PE gas pipelines ...
Scientific Research Publishing

BCN-YOLO: A Deep Learning Network for PCB Defect Detection ()

To address the issues of missed detection and false detection during the defect inspection process of the PCB, an improved YOLOv7-based algorithm for PCB defect detection is proposed. Firstly, 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 ...
C&EN

Image-Based Machine Learning Using Inkjet-Printed Chemicals: Mixing Ratio Prediction and Metal Ion Detection

Division of Applied Chemistry, Faculty of Engineering, Hokkaido University, Kita 13, Nishi 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan ...
GitHub

MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot Learning (ICCV2025)

This software is a research prototype, solely developed for and published as part of the publication MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot ...