Crack Analysis Tool in Python (CrackPy) - automatic detection and fracture mechanical analysis of (fatigue) cracks using digital image correlation
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Updated
Jul 24, 2024 - Python
Crack Analysis Tool in Python (CrackPy) - automatic detection and fracture mechanical analysis of (fatigue) cracks using digital image correlation
Crack Segmentation for Low-Resolution Images using Joint Learning with Super-Resolution (CSSR) was accepted to international conference on MVA2021 (oral), and selected for the Best Practical Paper Award.
Official code for ICIP 2023 paper "A Convolutional-Transformer Network for Crack Segmentation with Boundary Awareness"
This repository contains code and dataset for the task crack segmentation using two architectures UNet_VGG16, UNet_Resnet and DenseNet-Tiramusu
This repository contains some SIMPLE modules for Crack Detection and Semantic Segmentation.
DeepCrack: Learning Hierarchical Convolutional Features for Crack Detection
Here road crack detection was done using CNN with a large dataset.
Crack detection for concrete structures
A Pytorch implementation of DeepCrack and RoadNet projects.
Crack Detection On Highway Or Pavement Using OpenCV
Real time crack segmentation using PyTorch, OpenCV and ONNX runtime
This repo contains customized deep learning models for segmenting cracks.
Expandable crack detection for composite materials. To cite this Original Software Publication: https://www.sciencedirect.com/science/article/pii/S2352711021001205
finding cracks in highway using some pattern recognition and machine learning methods.
A python-based crack detection and classification system using deep learning; used YOLO object detection algorithm. To extract the features of cracks we used Computer Vision and developed a desktop tool using Kivy to display the outcomes.
A pre-trained MobileNet model for detecting cracks on concrete structures
Incorporating Inductive Bias into Deep Learning: A Perspective from Automated Visual Inspection in Aircraft Maintenance
A pre-trained MobileNet model for detecting cracks on concrete structures.
Wall wear segmentation using Convolutional Neural Networks
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