ETCI-2021-Competition-on-Flood-Detection
Pseudo-Labelling
ETCI-2021-Competition-on-Flood-Detection | Pseudo-Labelling | |
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1 | 1 | |
150 | 9 | |
- | - | |
1.8 | 0.0 | |
almost 2 years ago | almost 2 years ago | |
Jupyter Notebook | Jupyter Notebook | |
Apache License 2.0 | - |
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.
ETCI-2021-Competition-on-Flood-Detection
Pseudo-Labelling
What are some alternatives?
Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.
ganbert-pytorch - Enhancing the BERT training with Semi-supervised Generative Adversarial Networks in Pytorch/HuggingFace
unet - unet for image segmentation
PAWS-TF - Minimal implementation of PAWS (https://arxiv.org/abs/2104.13963) in TensorFlow.
TTS - :robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
semi-supervised-segmentation-on-graphs - Semi supervised segmentation on graphs (images and pointclouds). Using Eikonal equation.
PySyft - Perform data science on data that remains in someone else's server
cellpose - a generalist algorithm for cellular segmentation with human-in-the-loop capabilities
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
idx2numpy_array - Convert data in IDX format in MNIST Dataset to Numpy Array using Python