Pseudo-Labelling
Pseudo Labelling on MNIST dataset in Tensorflow 2.x (by consequencesunintended)
ETCI-2021-Competition-on-Flood-Detection
Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training (by sidgan)
Pseudo-Labelling | ETCI-2021-Competition-on-Flood-Detection | |
---|---|---|
1 | 1 | |
9 | 150 | |
- | - | |
0.0 | 1.8 | |
almost 2 years ago | almost 2 years ago | |
Jupyter Notebook | Jupyter Notebook | |
- | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Pseudo-Labelling
Posts with mentions or reviews of Pseudo-Labelling.
We have used some of these posts to build our list of alternatives
and similar projects.
ETCI-2021-Competition-on-Flood-Detection
Posts with mentions or reviews of ETCI-2021-Competition-on-Flood-Detection.
We have used some of these posts to build our list of alternatives
and similar projects.
What are some alternatives?
When comparing Pseudo-Labelling and ETCI-2021-Competition-on-Flood-Detection you can also consider the following projects:
ganbert-pytorch - Enhancing the BERT training with Semi-supervised Generative Adversarial Networks in Pytorch/HuggingFace
Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.
PAWS-TF - Minimal implementation of PAWS (https://arxiv.org/abs/2104.13963) in TensorFlow.
unet - unet for image segmentation
semi-supervised-segmentation-on-graphs - Semi supervised segmentation on graphs (images and pointclouds). Using Eikonal equation.
TTS - :robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
PySyft - Perform data science on data that remains in someone else's server
Pseudo-Labelling vs ganbert-pytorch
ETCI-2021-Competition-on-Flood-Detection vs Made-With-ML
Pseudo-Labelling vs PAWS-TF
ETCI-2021-Competition-on-Flood-Detection vs unet
Pseudo-Labelling vs semi-supervised-segmentation-on-graphs
ETCI-2021-Competition-on-Flood-Detection vs TTS
Pseudo-Labelling vs TTS
ETCI-2021-Competition-on-Flood-Detection vs PySyft