Implementation of the simCLR framework using the forward-forward algorithm
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Updated
Mar 4, 2024 - Python
Implementation of the simCLR framework using the forward-forward algorithm
Employ contrastive learning to enhance the ResNet-50 performace for skin lesion classification.
Implementation of the unsupervised SimCLR pre-training method.
Contrastive learning implementations using pyssl
Fork of Official Implementation of Meta-Learning to Improve Pre-Training, NeurIPS'21 Poster. (https://arxiv.org/abs/2111.01754)
Finetuning and clustering library for image perceptual similarity models.
Self-Supervised Learning approach to learn contrasting representation between images.
M.Sc.Eng Degree Project in Computer Science. 🌻
Adversarial Meta Learning on Contrastive Learning model SimCLR. Aiming to robustify original SimCLR with data augmentation and adversarial training.
A Simple Framework for Contrastive Learning of Visual Representations of pytorch implementation
Repository containing source code of the master thesis: "Synthetic Data and Contrastive Self-Supervised Training for Central Sulcus Segmentation"
Quick and simple Deep Learning projects for learning and experimenting. Ideal for beginners and those looking to practice AI concepts.
Official implementation of "Augmentation-aware Self-supervised Learning with Conditioned Projector"
A deep learning model that finds out dental malpractice from tooth x-ray images.
SimCLR implementation in Julia
Re-implementation of Intriguing Properties of Contrastive Losses paper
PyTorch implementation of SimCLR: Simple Framework for Contrastive Learning of Visual Representations by Chen et al. (2020)
Contrastive learning for unsupervised clustering, Semester project Spring 2022
A python library for self-supervised learning
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