Papers with Code 아카이브
Semi-Supervised Image Classification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 59
- 보존된 평가 기록
- 456
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/google-research/s4l
https://github.com/guerbet-ai/wsp-contrastive
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/hannaiiyanggit/unicon
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/hanzhanggit/StackGAN-inception-model
https://github.com/healthcare-robotics/mr-gan
https://github.com/helmy-elrais/Semi_Supervised_Learning
https://github.com/hemakaraveenhansika/convirt
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/hh-xiaohu/Image-augementation-pytorch
https://github.com/hiram64/temporal-ensembling-semi-supervised
https://github.com/hongyi-zhang/Fixup
https://github.com/hongyi-zhang/mixup
https://github.com/hsfzxjy/swavx
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
https://github.com/htdt/self-supervised
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/iejMac/ScriptWriter
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/ifsheldon/MPL_Lightning
https://github.com/ildoonet/unsupervised-data-augmentation
https://github.com/ilkhem/icebeem
https://github.com/isaacgerg/keras_odds_and_ends
https://github.com/iver56/audiomentations
https://github.com/jankrepl/mildlyoverfitted
https://github.com/jefflai108/Contrastive-Predictive-Coding-PyTorch
https://github.com/jeffwiroj/robust_tutorial
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
https://github.com/jhaprince/multibully
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/jianshen92/stanford-car-grab-challenge
https://github.com/jizongFox/DeepClusteringProject
Invariant Information Clustering for Unsupervised Image Classification and Segmentation
https://github.com/jmaronas/calibration_MixupDNN_ARCLoss.pytorch
https://github.com/joannayu25/NLP_Project_MIDS-W266
https://github.com/john-mlr/CIFAR-10-SimCLR
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/johnchenresearch/SSL
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
https://github.com/jonahanton/ssl_audio
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
https://github.com/jonnor/datascience-master
https://github.com/jqhoogland/rgpy
https://github.com/jramapuram/BYOL
Bootstrap your own latent: A new approach to self-supervised Learning
https://github.com/jramapuram/SimCLR
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/js-aguiar/wheat-object-detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.