Pinned Repositories
adversarial-segmentation
Anomaly detection on medical images. Unsupervised Segmentation of tumors usin GANs..
anogan-keras
Unsupervised anomaly detection with generative model, keras implementation
Anomaly-Detection-PatchSVDD-PyTorch
Anomaly-Detection-with-GAN
Steel defect detection intern project in PIRL(Postech information Research Laboratories)
AnomalyDetection
Anomaly Detection in computer vision
DefectDetection
Implementation of papers concerned with anolmaly/defect segmentation with Neural Networks
FabricDefectDetection
AIFT2019-Real-time fabric defect segmentation based on convolutional neural network
Ganomaly-pytorch
关于杜伦大学的GANomaly的代码
Industrial-Defect-Inspection-segmentation
Automatic Defect Inspection with End-to-End Deep Learning
pytorch-book
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)
yixiyixi5's Repositories
yixiyixi5/FabricDefectDetection
AIFT2019-Real-time fabric defect segmentation based on convolutional neural network
yixiyixi5/Industrial-Defect-Inspection-segmentation
Automatic Defect Inspection with End-to-End Deep Learning
yixiyixi5/pytorch-book
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)
yixiyixi5/adversarial-segmentation
Anomaly detection on medical images. Unsupervised Segmentation of tumors usin GANs..
yixiyixi5/Anomaly-Detection-PatchSVDD-PyTorch
yixiyixi5/AnomalyDetection
Anomaly Detection in computer vision
yixiyixi5/AutoEncoder-SSIM-for-unsupervised-anomaly-detection-
Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders
yixiyixi5/context_encoder_pytorch
PyTorch Implement of Context Encoders: Feature Learning by Inpainting
yixiyixi5/Defect_Segmentation
An implementation of the U-net model based on the paper
yixiyixi5/DefectSegNet
DefectSegNet for semantic segmentation of defects in Steels
yixiyixi5/examples
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
yixiyixi5/f-AnoGAN
Code for reproducing f-AnoGAN training and anomaly scoring
yixiyixi5/f-AnoGAN-1
Implementation of f-AnoGAN with PyTorch
yixiyixi5/f-AnoGAN_with_Pytorch
yixiyixi5/FabricDefect
A weakly annotated fabric defect dataset. Contains 24 512x512 images. Every image has a 512x512 mask. The mask has one rectangular bounding box covering the entire defect but has pixels of fabric without defect. This makes the defect detection task challenging.
yixiyixi5/GAN-defect
demo project of <A Surface Defect Detection Method Based on Positive Samples>, deployed in pytorch
yixiyixi5/ganomaly
GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training
yixiyixi5/imgaug
Image augmentation for machine learning experiments.
yixiyixi5/ITAE-Pytorch-Anomaly_Detection
An unofficial implementation of 'Inverse-Transform AutoEncoder for Anomaly Detection', paper see https://arxiv.org/abs/1911.10676
yixiyixi5/PConv-Keras
Unofficial implementation of "Image Inpainting for Irregular Holes Using Partial Convolutions". Try at: www.fixmyphoto.ai
yixiyixi5/pytorch-CycleGAN-and-pix2pix
Image-to-Image Translation in PyTorch
yixiyixi5/Pytorch-Segmentation-multi-models
Pytorch implementation for Semantic Segmentation with multi models (Deeplabv3, Deeplabv3_plus, PSPNet, UNet, UNet_AutoEncoder, UNet_nested, R2AttUNet, AttentionUNet, RecurrentUNet,, SEGNet, CENet, DsenseASPP, RefineNet, RDFNet)
yixiyixi5/Pytorch-UNet
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
yixiyixi5/sae
An Auto-Encoder Strategy for Adaptive Image Segmentation (SAE)
yixiyixi5/Severstal-Steel-Defect-Detection-1
Can you detect and classify defects in steel? Segmentation in Pytorch
yixiyixi5/skip-ganomaly
Source code for Skip-GANomaly paper
yixiyixi5/tensorflow2_tutorials_chinese
tensorflow2中文教程，持续更新(当前版本:tensorflow2.0)，tag: tensorflow 2.0 tutorials
yixiyixi5/unet_magnetic_tiles_defects
Blow hole defects segmentation using UNet
yixiyixi5/Unsupervised_Anomaly_Detection_Brain_MRI
Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study
yixiyixi5/VAEGAN
try VAE GANLoss + SSIM loss in anomaly Detection