Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
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Updated
May 10, 2024 - Python
Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks
A contrastive learning based semi-supervised segmentation network for medical image segmentation
Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.
A state-of-the-art semi-supervised method for image recognition
FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai
Unsupervised Data Augmentation (UDA)
😎 An up-to-date & curated list of awesome semi-supervised learning papers, methods & resources.
Algorithms for outlier, adversarial and drift detection
GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training
A PyTorch-based library for semi-supervised learning (NeurIPS'21)
Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"
A Tensorflow implementation of Semi-supervised Learning Generative Adversarial Networks (NIPS 2016: Improved Techniques for Training GANs).
A Unified Semi-Supervised Learning Codebase (NeurIPS'22)
A PyTorch toolbox for domain generalization, domain adaptation and semi-supervised learning.
Code for the AAAI 2018 publication "SEE: Towards Semi-Supervised End-to-End Scene Text Recognition"
Code for the paper STN-OCR: A single Neural Network for Text Detection and Text Recognition
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
Adversarial Learning for Semi-supervised Semantic Segmentation, BMVC 2018
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