Ecosyste.ms: Repos
An open API service providing repository metadata for many open source software ecosystems.
GitHub topics: wafer-defects
Burhan-Q/ClassifyDefectMap_MixedWM38
Classification of wafer defect map patterns
Language: Python - Size: 8.48 MB - Last synced: about 2 months ago - Pushed: about 1 year ago - Stars: 5 - Forks: 0
kannanjayachandran/Wafers-Fault-Detection
End to end machine learning project to detects fault in the wafers based on sensor data
Language: Python - Size: 1.08 MB - Last synced: 5 months ago - Pushed: 5 months ago - Stars: 12 - Forks: 4
vignes-12/senior-design-project-28-wafer-defect-detection
This project aims to process 2D images of semiconductor silicon wafers to identify any defects on the wafers as well as their corresponding locations.
Language: Python - Size: 295 MB - Last synced: 6 months ago - Pushed: about 1 year ago - Stars: 3 - Forks: 0
PanithanS/MixedType-Wafers-Defect-Recognition-with-Visual-Transformer
We use MixedWM38, the mixed-type wafer defect pattern dataset for wafer defect pattern regcognition with visual transformers.
Language: Jupyter Notebook - Size: 188 KB - Last synced: 8 months ago - Pushed: 8 months ago - Stars: 0 - Forks: 0
suryanshyaknow/faulty-wafer-component-detection
data fetched by wafers (thin slices of semiconductors) is to be passed through the machine learning pipeline and it is to be determined whether the wafer at hand is faulty or not. Wafers are predominantly used to manufacture solar cells and are located at remote locations in bulk and they themselves consist of few hundreds of sensors.
Language: Jupyter Notebook - Size: 4.2 MB - Last synced: over 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0
JNewman-cell/WaferMapNeuralNetworkClassification
This is a neural network designed to classify wafer imperfections without feature engineering.
Language: Jupyter Notebook - Size: 1.62 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0
suryanshyaknow/wafer-fault-detection
data fetched by wafers (thin slices of semiconductors) is to be passed through the machine learning pipeline and it is to be determined whether the wafer at hand is faulty or not. Wafers are predominantly used to manufacture solar cells and are located at remote locations in bulk and they themselves consist of few hundreds of sensors.
Language: Jupyter Notebook - Size: 3.6 MB - Last synced: over 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0
Anil-45/Faulty_wafer_detection
Faulty Wafer Detection
Language: Python - Size: 585 KB - Last synced: 12 months ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0
