SteliosTsop / QF-image-segmentation-kerasLinks
In this repository, we present an Semantic Segmentation code, based on U-net architecture, that is used for the topographic characterization of the fracture surfaces of brittle materials. The results of this work are presented in the publication: " Toward quantitative fractography using convolutional neural networks ".
☆15Updated 4 years ago
Alternatives and similar repositories for QF-image-segmentation-keras
Users that are interested in QF-image-segmentation-keras are comparing it to the libraries listed below
Sorting:
- Concrete Crack and Spalling Detection using Deep Neural Network☆86Updated 6 years ago
- Crack detection for concrete structure using Matlab☆32Updated 8 years ago
- Author's implementation of A deep convolutional neural network for rock fracture image segmentation☆27Updated 3 years ago
- Different modeling techniques like multiple linear regression, decision tree, and random forest, etc. will be used for predicting the co…☆24Updated 5 years ago
- ☆15Updated 5 years ago
- A Deep Learning Humerus Bone Fracture Detection Model which classifies a broken humerus bone X-ray image from a normal X-ray image with n…☆14Updated 5 years ago
- Crack Analysis Tool in Python (CrackPy) - automatic detection and fracture mechanical analysis of (fatigue) cracks using digital image co…☆83Updated last year
- Benchmark problems of GPU computing of phase-field models☆13Updated 2 years ago
- GAN/convolutional and Transformer models to predict missing mechanical information given limited known data in part of the domain, and fu…☆20Updated 2 years ago
- Adaptive phase field modeling of fracture using deep energy minimization.☆34Updated 4 years ago
- Incorporating Inductive Bias into Deep Learning: A Perspective from Automated Visual Inspection in Aircraft Maintenance☆57Updated 5 years ago
- Physics-informed neural network for fatigue crack propagation (Paris' law)☆16Updated 3 years ago
- Prediction and control of fracture paths in disordered architected materials using graph neural networks☆12Updated 2 years ago
- This project aims at the problem of road surface image denoising and crack recognition by using embedded camera. Using Gaussian filter to…☆12Updated last year
- Segmentation of different types of bones using Thresholding and morphological operations and detected (located) fracture using Hough Tran…☆10Updated 5 years ago
- Develop the time series recurrent neural network algorithms using LSTM and ARIMA in order 1) to forecast oil production of existing wells…☆12Updated 5 years ago
- Code to the Publication Meshfree Simulation of Metal Cutting: An Updated Lagrangian Approach with Dynamic Refinement☆13Updated 6 years ago
- priyamittal15 / Implementation-of-Different-Deep-Learning-Algorithms-for-Fracture-Detection-Image-ClassificationUsing-Deep-Learning-Techniques-perform-Fracture-Detection-Image-Processing Using Different Image Processing techniques Implementing Fract…☆14Updated 3 years ago
- ☆37Updated 7 years ago
- An application FCN for crack recogntion using tensorflow☆49Updated 7 years ago
- Deep learning model to predict complex stress and strain fields in hierarchical composites☆28Updated 2 years ago
- ☆10Updated 4 years ago
- The project uses Unet-based improved networks to study road crack segmentation, which is based on keras.☆44Updated 5 years ago
- MeltpoolNet: Melt pool Characteristic Prediction in Metal Additive Manufacturing Using Machine Learning☆36Updated 3 years ago
- Graph neural networks for stress and strain fields prediction☆52Updated 2 years ago
- A MATLAB/C++ implementation of solid texture synthesis algorithms for constructing statistically representative 3D microstructure dataset…☆29Updated 8 years ago
- Code: A phase field formulation for dissolution-driven stress corrosion cracking (https://doi.org/10.1016/j.jmps.2020.104254)☆13Updated 2 years ago
- Stress Field Prediction in Cantilevered Structures Using Convolutional Neural Networks☆33Updated 5 years ago
- An application of CNN for crack detection using Caffe☆11Updated 5 years ago
- Predicting 2D Steady State Fluid Flow Fields using Convolutional Neural Networks☆10Updated 4 years ago