The system, developed by Panevo, a Canadian clear technology and manufacturing analytics company, reportedly achieved approximately 97% detection reliability with minimal false positives of Muskoka’s ...

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/ ├── ...

PCB(Printed Circuit Board) 제조 공정에서 발생하는 다양한 결함을 자동으로 검출하는 딥러닝 기반 객체 인식 시스템입니다. PCB/ ├── dataset/ # 데이터셋 │ ├── roboflow/ # Primary dataset (Roboflow format ...

Abstract: Printed circuit board (PCB) surface defect detection is crucial for ensuring product quality and improving production efficiency. In recent years, deep learning-based methods have achieved ...

Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine-learning algorithm designed to identify physical anomalies in solar ...

Doctors in the Raquel and Jaime Gilinski Department of Obstetrics, Gynecology and Reproductive Science at Mount Sinai have become the first in New York City to implement an artificial intelligence (AI ...

They look, move and even smell like the kind of furry Everglades marsh rabbit a Burmese python would love to eat. But these bunnies are robots meant to lure the giant invasive snakes out of their ...