[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning
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Updated
Apr 3, 2021 - Python
[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning
ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation (CVPR20)
Python codes for weakly-supervised learning
Code release for "Learning to Detect Mobile Objects from LiDAR Scans Without Labels" [CVPR 2022]
Improving Human Activity Recognition through Self-training with Unlabeled Data
One Line To Build Zero-Data Classifiers in Minutes
[ICML 2024] Offical code repo for ICML2024 paper "Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data"
📸 Face Clustering Engine developed using OpenCV & DBSCAN, deployed as a Streamlit Web App to deliver uploaded images grouped according to the individual unique faces in them.
Caffe implementation of "Learning Compression from Limited Unlabeled Data" (ECCV2018).
A Pytorch implementation of the MixMatch algorithm developed by google-research.
Supervised learning on unbalanced data
Keras/Tensorflow implementation for co-generation and segmentation of surgical instruments using unlabelled robot-assisted surgery data.
Mongolian Polarity Detection in Weakly Supervised manner
[TMLR 22] "Queried Unlabeled Data Improves and Robustifies Class- Incremental Learning" by Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Animi, Zhangyang Wang
"Snorkel with Turtle" is a realtime labeling system based on Snorkel
Best Clustering using silhouette_score
Stress Detection in Social Media
Semi-PKD: Semi-supervised Pseudoknowledge Distillation for saliency prediction
Model Distillation for Unlabeled and Imbalanced Data for Amino-Acid-Strings
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