Papers with Code 아카이브
Unsupervised Domain Adaptation
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Unsupervised Domain Adaptation is a learning framework to transfer knowledge learned from source domains with a large number of annotated training examples to target domains with unlabeled data only.
Source: Domain-Specific Batch Normalization for Unsupervised Domain Adaptation
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/TrinhQuocNguyen/CORE-ReID
https://github.com/TrinhQuocNguyen/CORE-ReID-v2
https://github.com/Trustworthy-AI-Group/TransferAttack
Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer
https://github.com/UnofficialJuliaMirror/DeepMark-deepmark
https://github.com/UnofficialJuliaMirrorSnapshots/DeepMark-deepmark
https://github.com/Vaishnvi/ILLUME
https://github.com/Vamshi399/CarND-Vehicle-Detection
https://github.com/VamsiKrishna1211/gender_age-detection
https://github.com/VhalPurohit/290s
https://github.com/VinayBN8997/ResNet-CIFAR10
https://github.com/VisionLearningGroup/DA_Detection
Strong-Weak Distribution Alignment for Adaptive Object Detection
https://github.com/VisionLearningGroup/visda21-dev
https://github.com/ViswanathaReddyGajjala/EfficientNet-RetinaNet
https://github.com/WinChua/CDRTR
https://github.com/WuRui-Ella/Myfirststore
Joint Discriminative and Generative Learning for Person Re-identification
https://github.com/YudeWang/UNet-Satellite-Image-Segmentation
https://github.com/Zachdr1/CNNs
https://github.com/abaietto/neural_ode_classification
https://github.com/abuchin/resnet_sign
https://github.com/aby2s/sharpmask
https://github.com/adapt-python/adapt
https://github.com/adldotori/ResNet
https://github.com/ajaystar8/PDRUNet-PyTorch
https://github.com/ajgallego/dann
Incremental Unsupervised Domain-Adversarial Training of Neural Networks
https://github.com/ajithvallabai/getsetgo_keras-beginner
https://github.com/akamaster/pytorch_resnet_cifar10
https://github.com/akar5h/Image-Recognition-with-CNN-and-Transfer-Learning-ResNet101
https://github.com/akhadangi/EM-net
https://github.com/akommini/Spoken-Numeric-Digit-detection
https://github.com/alalagong/LEDNet
https://github.com/albert0147/nrc_sfda
Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation
https://github.com/albert0147/sfda_neighbors
Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation
https://github.com/albumentations-team/albumentations
https://github.com/alecwangcq/KFAC-Pytorch
https://github.com/alex-f1tor/Image-Caption
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.