Noisy-Labels-with-Bootstrapping
Deep learning on noisy data
An implementation of training deep neural networks on noisy labels with bootstrapping using Keras
Keras implementation of Training Deep Neural Networks on Noisy Labels with Bootstrapping, Reed et al. 2015
22 stars
2 watching
7 forks
Language: Python
last commit: over 5 years agodeep-learningnoisy-labels
Related projects:
| Repository | Description | Stars |
|---|---|---|
 delchiaro/training-cnn-noisy-labels-keras | An implementation of a deep learning training method for handling noisy labels in convolutional neural networks using the VGG-16 network architecture. | 6 |
 gorkemalgan/deep_learning_with_noisy_labels_literature | A collection of papers and repos on deep learning with noisy labels. | 235 |
 ryo-ito/noisy-labels-neural-network | An implementation of a neural network training method using noisy labels | 5 |
 udibr/noisy_labels | This project explores how to adapt neural networks to noisy labels by introducing a mechanism that can learn to correct the errors. | 118 |
 chenpf1025/noisy_label_understanding_utilizing | An investigation into deep learning models trained with noisy labels and methods to improve their accuracy. | 90 |
 kthyeon/fine_official | Implementation of a method to improve machine learning models trained with noisy labels by selecting and collaborating with high-quality samples | 39 |
 vdenberg/noisy-label-neural-network | An implementation of a neural network algorithm designed to improve performance on noisy labeled data | 3 |
 cysu/noisy_label | A repository providing code and scripts for training image classification models on noisy labeled data | 116 |
 xiaoboxia/t-revision | A PyTorch implementation of a method for learning with noisy labels in deep neural networks | 97 |
| chenpf1025/idn | Provides tools and data for studying instance-dependent label noise in deep neural networks, with a focus on combating noisy labels | 35 |
 uds-lsv/multi-tasking_learning_with_unreliable_labels | An open source software project that extends an existing algorithm to handle noisy labels in machine learning for low-resource data generation. | 8 |
 weijiaheng/advances-in-label-noise-learning | A curated collection of papers and resources on learning with noisy labels in machine learning | 696 |
 nust-machine-intelligence-laboratory/jo-src | An implementation of a contrastive learning approach to address noisy labels in machine learning models | 5 |
 ijindal/noisy_dropout_regularization | This project explores training deep neural networks using noisy labels with dropout regularization to improve robustness. | 11 |
 pokaxpoka/rognoisylabel | A Python package for robust inference via generative classifiers for handling noisy labels in machine learning. | 33 |