Unsupervised-Classification
cs231n
| Unsupervised-Classification | cs231n | |
|---|---|---|
| 2 | 1 | |
| 1,308 | - | |
| - | - | |
| 1.4 | - | |
| 9 months ago | - | |
| Python | ||
| GNU General Public License v3.0 or later | - |
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Unsupervised-Classification
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Middle ground dataset between CIFAR and ImageNet [D]
The subsets we used are from here: https://github.com/wvangansbeke/Unsupervised-Classification/tree/master/data/imagenet_subsets
- Any reference or idea about how to train unsupervised CNN model ?
cs231n
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Any reference or idea about how to train unsupervised CNN model ?
If you really want a coding notebook to walk you through this to learn how to do this on your own, check out assignment 3 Q5 of Stanford cs231n https://github.com/cs231n/cs231n.github.io/tree/master/assignments/2020
What are some alternatives?
simclr - SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners
self-supervised - Whitening for Self-Supervised Representation Learning | Official repository
Unsupervised-Semantic-Segmentation - Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals. [ICCV 2021]
contrastive-reconstruction - Tensorflow-keras implementation for Contrastive Reconstruction (ConRec) : a self-supervised learning algorithm that obtains image representations by jointly optimizing a contrastive and a self-reconstruction loss.
DiffCSE - Code for the NAACL 2022 long paper "DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings"
Transformer-SSL - This is an official implementation for "Self-Supervised Learning with Swin Transformers".
vectorrvnn - Data Driven method for hierarchical grouping of paths in Vector Graphics.
SimMIM - This is an official implementation for "SimMIM: A Simple Framework for Masked Image Modeling".
PASS - The PASS dataset: pretrained models and how to get the data
PaddleHelix - Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集
Clover - An Efficient DNA Clustering algorithm based on Tree Structure.