sbelharbi / deep-active-learning-for-joint-classification-and-segmentation-with-weak-annotator
Pytorch code for the paper "Deep Active Learning for Joint Classification and Segmentation with Weak Annotator"
☆29Updated 2 years ago
Alternatives and similar repositories for deep-active-learning-for-joint-classification-and-segmentation-with-weak-annotator:
Users that are interested in deep-active-learning-for-joint-classification-and-segmentation-with-weak-annotator are comparing it to the libraries listed below
- PyTorch implementation of Foveation for Segmentation of Ultra-High Resolution Images☆41Updated 2 years ago
- This page is for A Survey on Deep Learning of Small Sample in Biomedical Image Analysis.☆28Updated 4 years ago
- The implementation of "Semi-supervised Medical Image Classification with Global Latent Mixing". [MICCAI2020]☆21Updated last year
- Offical code for 'Few-Shot Anomaly Detection for Polyp Frames from Colonoscopy' [MICCAI 2020]☆20Updated 3 years ago
- Loss functions for Image Segmentation☆12Updated 4 years ago
- ☆21Updated 4 years ago
- Assessing Reliability and Challenges of Uncertainty Estimations for Medical Image Segmentation☆53Updated last year
- A repository for semi supervised image segmentation using Mean Teacher☆29Updated 5 years ago
- Code of our method MbLS (Margin-based Label Smoothing) for network calibration. To Appear at CVPR 2022. Paper : https://arxiv.org/abs/211…☆49Updated 2 years ago
- ☆36Updated 2 years ago
- Pre-trained model, code, and materials from the paper "Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmen…☆58Updated 4 years ago
- The official implementation of "CateNorm: Categorical Normalization for Robust Medical Image Segmentation"☆32Updated 2 years ago
- Unsupervised medical image segmentation using edge mapping and adversarial learning☆20Updated 5 years ago
- Gcam is an easy to use Pytorch library that makes model predictions more interpretable for humans. It allows the generation of attention…☆49Updated 4 years ago
- ☆21Updated 4 years ago
- Code for the MICCAI DART 2020 paper☆33Updated 3 years ago
- A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in Different Image Domains (IJCV submission)☆49Updated 4 years ago
- [NeurIPS 2020] Disentangling Human Error from the Ground Truth in Segmentation of Medical Images☆71Updated last year
- ☆8Updated last year
- The source code of 'Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image Classification' (MICCAI 2021)☆17Updated 3 years ago
- Official Pytorch implementation of the paper DeScarGAN☆30Updated 4 years ago
- Learns effective selective labeling strategies for medical images using deep reinforcement learning and meta learning☆25Updated 3 years ago
- Code for our method MaskSplit. Paper is available at https://arxiv.org/abs/2110.12207.☆19Updated 3 years ago
- ☆11Updated 3 years ago
- Code for meta-learning initializations for image segmentation☆31Updated 3 years ago
- Repository for implementation of active learning and semi-supervised learning algorithms and applying them to medical imaging datasets☆16Updated 3 years ago
- Supervised and unsupervised loss functions for image segmentation based on the classical FCM objective function. (TensorFlow and PyTorch)☆16Updated 3 years ago
- Implementation of active learning features for AxonDeepSeg software (axon-myelin segmentation)☆38Updated 6 years ago
- Code for our arxiv preprint: https://arxiv.org/abs/1904.05236☆34Updated 5 years ago