Code for TKDE paper "Self-supervised learning on graphs: Contrastive, generative, or predictive"

This repository is mainly dedicated for listing the recent research advancements in the application of Self-Supervised-Learning in medical images computing field

[TNSRE 2023] Self-supervised Learning for Label-Efficient Sleep Stage Classification: A Comprehensive Evaluation

Overview of unsupervised visual representation learning (or self-supervised learning, unsupervised pre-training) methods.

A python implementation of “Self-Supervised Learning of Spatial Acoustic Representation with Cross-Channel Signal Reconstruction and Multi-Channel Conformer” [TASLP 2024]

[IEEE T-IP 2022] TCGL: Temporal Contrastive Graph for Self-supervised Video Representation Learning

One-class classification approach using error of image transformation into one image

[NN2024] FullRot + WRMix: Any Region Can Be Perceived Equally and Effectively on Rotation Pretext Task Using Full Rotation and Weighted-Region Mixture

Comparison of Feature Extraction Methods on Free-hand Sketches

Deep Learning Course | Home Works | Spring 2021 | Dr. MohammadReza Mohammadi

Overview of self-supervised video representation learning methods.

Pre-text pre-training -> image segmentaion pipelines. Utilize contrastive learning and ViT as Encoder. Studied the effects of dataset sizes, dataset similarity and effects of fine-tuning.