📈 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 of surface defect research which are of great importance.

Chemical intuition for surface science in a package.

The core code of AGCA: An Adaptive Graph Channel Attention Module for Steel Surface Defect Detection

CTSegNet is an end-to-end 3D segmentation package for large X-ray tomographic datasets using 2D fully convolutional neural networks (fCNN).

The re-labeled NRSD-MN dataset, AMFF-YOLOX source code and paper "AMFF-YOLOX: Towards an Attention Mechanism and Multiple Feature Fusion Based on YOLOX for Industrial Defect Detection".

An application to create 2D geometry. A flexible user-friendly application to create 2D objects (points, curves and surfaces).

缺陷检测文献记录

Detect featured surfaces of unstructured meshed.

（最先进的缺陷检测网络） A Tensorflow implementation of "Segmentation-Based Deep-Learning Approach for Surface-Defect Detection"

Salient Object Detection: A Benchmark

This project automates paper defect localization in industrial quality control using feature extraction and machine learning. Techniques include HOG, Gabor filters, Canny edge detection, and Wavelet Transform with SVMs, CNNs, and ensemble learning. It aims to reduce manual inspection, improving efficiency and reliability in defect detection.

The App allows you to measure the distance between two points in space.

This is an anomaly detection classification algorithm based on CNN based approach

Pytorch Implement of the paper "Segmentation-Based Deep-Learning Approach for Surface Defect Detection"

C# implementation of random closed domain generator

导光板缺陷检测(a simple mura detect project)

Ming-Ming Cheng's open source projects

基于Deeplabv3+的钢铁分割实验

Pytorch implementation of Real Time Image Saliency for Black Box Classifiers https://arxiv.org/abs/1705.07857

Exploiting surroundedness for saliency detection: a boolean map approach