PanithanS/Wafers-Defect-Recognition-using-Visual-Transformer
We use MixedWM38, the mixed-type wafer defect pattern dataset for wafer defect pattern regcognition with visual transformers.
This helps semiconductor manufacturers quickly identify and classify defects on silicon wafers during production. You provide images of wafer maps, and it tells you the specific type of defect present, even if multiple types occur together. This helps quality control engineers and operations managers understand root causes, reduce waste, and improve product quality.
No commits in the last 6 months.
Use this if you need an automated system to accurately classify various single and mixed defect patterns on semiconductor wafers to enhance manufacturing efficiency and yield.
Not ideal if you are looking for a system to detect new, previously unseen defect types rather than classifying known patterns.
Stars
44
Forks
14
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Oct 01, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/PanithanS/Wafers-Defect-Recognition-using-Visual-Transformer"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Charmve/Surface-Defect-Detection
📈 目前最大的工业缺陷检测数据库及论文集 Constantly summarizing open source dataset and critical papers in the field...
aviralchharia/Surface-Defect-Detection-in-Hot-Rolled-Steel-Strips
This project aims to automatically detect surface defects in Hot-Rolled Steel Strips such as...
memari-majid/Wind-Turbine-Blade-Defect-Detection-with-YOLO-Models
Defect Detection with YOLO Family Models
hafidh561/steel-defect-detection
Steel defect detection is a function of segmentation of defect area in steel surfaces using a camera
cosminpm/bottle-caps-backend
Detection and dentification of bottle caps.