pohwa065 / Surface-Defect-Image-Classification-with-Convolutional-Neural-NetworkLinks
The proposed idea is to use convolutional neural network (CNN) to classify defects on the semiconductor wafer substrate. There are total 7 classes to be classified. Data augmentation by Generative Adversarial Network (GAN) is applied on 2 of the classes to improve classification accuracy.
☆18Updated 4 years ago
Alternatives and similar repositories for Surface-Defect-Image-Classification-with-Convolutional-Neural-Network
Users that are interested in Surface-Defect-Image-Classification-with-Convolutional-Neural-Network are comparing it to the libraries listed below
Sorting:
- Segmentation-Based Deep-Learning Approach for Surface-Defect Detection☆26Updated 4 years ago
- generate randomly defects on positive samples and restore them with GAN.☆40Updated 4 years ago
- Steel defect detection intern project in PIRL(Postech information Research Laboratories)☆18Updated 6 years ago
- Unsupervised-Defect-Segmentation anomaly detection☆30Updated 5 years ago
- ☆24Updated 6 years ago
- This is a deep learning application project in the industrial field, intended to detect defects on the workpiece surface. The code is bas…☆83Updated 5 years ago
- Segmentation-based deep-learning approach for surface-defect detection with pytorch☆25Updated 8 months ago
- This is the GC10-DET datasets of the upcoming paper " Deep Metallic Surface Defect Detection: the New Benchmark and Detection Network" Th…☆67Updated 3 years ago
- demo project of <A Surface Defect Detection Method Based on Positive Samples>, deployed in pytorch☆42Updated 5 years ago
- ⚡Saliency detection for strip steel surface defects using multiple constraints and improved texture features☆35Updated 5 years ago
- try VAE GANLoss + SSIM loss in anomaly Detection☆13Updated 5 years ago
- ⚡EDRNet:Encoder-Decoder Residual Network for Salient Object Detection of Strip Steel Surface Defects☆53Updated 4 years ago
- This is Keras code from "Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders".☆53Updated 6 years ago
- This repo contains data pre-processing, classification and defect detection methodologies for images from Advance XRay Inspection from mu…☆56Updated 4 years ago
- Open-source code for our CVPR19 paper "Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification w…☆74Updated 5 years ago
- ☆28Updated 3 years ago
- Dataset for classification, detection and prognostics of surface defects on ball screw drives☆68Updated 4 years ago
- LF-YOLO (Lighter and Faster YOLO) is used to detect defect of X-ray weld image.☆62Updated last year
- Implemention of the paper "Anomaly Detection of Defect using Energy of Point Pattern Features within Random Finite Set Framework"☆13Updated 3 years ago
- This is the implementation of Semi-supervised Anomaly Detection using AutoEncoders☆62Updated 5 years ago
- Project: Unsupervised Anomaly Segmentation via Deep Feature Reconstruction☆97Updated 3 years ago
- dataset of the upcoming paper "Saliency of magnetic tile surface defects"☆198Updated 5 years ago
- This is a segmentation network based on good old EfficientNet, with a twist...☆29Updated 2 years ago
- DefectNet: Towards Fast and Effective Defect Detection☆21Updated 2 years ago
- 玻璃绝缘子缺陷检测☆33Updated 4 years ago
- Pytorch Implement of the paper "Segmentation-Based Deep-Learning Approach for Surface Defect Detection"☆195Updated 5 years ago
- ☆17Updated 6 years ago
- Surface Defect Detection with Segmentation-Decision Network on KolektorSDD☆137Updated 4 years ago
- This is an unofficial implementation of ' Anomaly localization by modeling perceptual features'☆23Updated 4 years ago
- ☆45Updated 3 years ago