https://github.com/yanzhicong/mixup_ssl
Interpolation Consistency Training for Semi-Supervised Learning
Papers with Code 아카이브
Semi-Supervised Image Classification
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Semi-supervised image classification leverages unlabelled data as well as labelled data to increase classification performance.
You may want to read some blog posts to get an overview before reading the papers and checking the leaderboards:
- An overview of proxy-label approaches for semi-supervised learning - Sebastian Ruder
- Semi-Supervised Learning in Computer Vision - Amit Chaudhary
<span style="color:grey; opacity: 0.6">( Image credit: Self-Supervised Semi-Supervised Learning )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yaox12/BYOL-PyTorch
Bootstrap your own latent: A new approach to self-supervised Learning
https://github.com/yell/kaggle-camera
https://github.com/ylqi/count-anything
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/ymittal23/PlayWithCifar
Improved Regularization of Convolutional Neural Networks with Cutout
https://github.com/yoojungsun0/Psych239
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/yuleiqin/capro
https://github.com/yuleiqin/fopro
https://github.com/yusuke0519/constrastive_predictive_coding
https://github.com/yuuun/clip_pytorch
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/yuxi120407/mixmatch_tensorflow
https://github.com/yuxi120407/semi-supervised_tensorflow2.0
https://github.com/zcao0420/moformer
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
https://github.com/zcemycl/Matlab-GAN
Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks
https://github.com/zer0sh0t/artificial_intelligence/tree/master/self_supervised_learning_methods/bootstrap_your_own_latent
Bootstrap your own latent: A new approach to self-supervised Learning
https://github.com/zhangqinghao0811/unpool
https://github.com/zhangxu0963/npc
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/zhenxuan00/triple-gan
https://github.com/zhirongw/lemniscate.pytorch
https://github.com/ziqiao-shang/aunce
https://github.com/zll17/Neural_Topic_Models
Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks
https://github.com/zpf0117b/CLMB
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/zwenyu/UniSSDA
https://github.com/zysymu/AdaMatch-pytorch
ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring
https://gitlab.com/birder/birder
Bootstrap your own latent: A new approach to self-supervised Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.