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#

pseudo-labeling

Here are 60 public repositories matching this topic...

code released for our ICML 2020 paper "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation"

  • UpdatedFeb 22, 2024
  • Python

PyTorch open-source toolbox for unsupervised or domain adaptive object re-ID.

  • UpdatedJun 14, 2021
  • Python

Winning solution for the Kaggle TGS Salt Identification Challenge.

  • UpdatedAug 8, 2019
  • Python

TGS Salt Identification

  • UpdatedAug 30, 2024
  • Python

"In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning" by Mamshad Nayeem Rizve, Kevin Duarte, Yogesh S Rawat, Mubarak Shah (ICLR 2021)

  • UpdatedMay 17, 2023
  • Python

[NAACL 2021] This is the code for our paper `Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach'.

  • UpdatedAug 17, 2022
  • Python

Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training

  • UpdatedJun 19, 2022
  • Jupyter Notebook

PromptDet: Towards Open-vocabulary Detection using Uncurated Images, ECCV2022

  • UpdatedSep 18, 2022
  • Python

[IJCAI 2022] Official Pytorch code for paper “S2 Transformer for Image Captioning”

  • UpdatedAug 14, 2024
  • Python

Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling

  • UpdatedJan 29, 2022
  • MATLAB

[IJCAI 2023] Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation

  • UpdatedMay 14, 2024
  • Python

[NeurIPS 2022] Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering

  • UpdatedOct 6, 2023
  • Python

Semi-Supervised Hyperspectral Image Classification

  • UpdatedAug 11, 2022
  • Python

The dataset for the paper 'Learning self-supervised traversability with navigation experiences of mobile robots: A risk-aware self-training approach'

  • UpdatedOct 24, 2024
  • CMake

"OpenLDN: Learning to Discover Novel Classes for Open-World Semi-Supervised Learning" by Mamshad Nayeem Rizve, Navid Kardan, Salman Khan, Fahad Shahbaz Khan, Mubarak Shah (ECCV 2022)

  • UpdatedMar 14, 2023
  • Python

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