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Unsupervised Domain Adaptation

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하위 태스크: 1
평가표: 49
보존된 평가 기록: 393

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/asahi417/DeepDomainAdaptation

Domain-Adversarial Training of Neural Networks

https://github.com/ascust/MADA

Regularizing Proxies with Multi-Adversarial Training for Unsupervised Domain-Adaptive Semantic Segmentation

https://github.com/ashishpatel26/BrainMRI-Segmentation-Keras

Deep Residual Learning for Image Recognition

https://github.com/asprenger/keras_fc_densenet

Deep Residual Learning for Image Recognition

https://github.com/astoycos/Mini_Project2

Deep Residual Learning for Image Recognition

https://github.com/attm/tensorflow_advent

ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation

https://github.com/aurelien-peden/Deep-Learning-paper-implementations

Deep Residual Learning for Image Recognition

https://github.com/avocardio/resnet_vs_convnext

Deep Residual Learning for Image Recognition

https://github.com/axmoyal/Steganalysis-with-CNN

Deep Residual Learning for Image Recognition

https://github.com/b8goal/PIRL-Residual-network

Deep Residual Learning for Image Recognition

https://github.com/barmayo/spatial_attention

Deep Residual Learning for Image Recognition

https://github.com/bbdamodaran/deepJDOT

DeepJDOT: Deep Joint Distribution Optimal Transport for Unsupervised Domain Adaptation

https://github.com/bclwan/MRI_Brain_Segmentation

Deep Residual Learning for Image Recognition

https://github.com/ben-davidson-6/fixup

Deep Residual Learning for Image Recognition

https://github.com/bentrevett/pytorch-image-classification

Deep Residual Learning for Image Recognition

https://github.com/bertrandlalo/deep_dog_breeds

Deep Residual Learning for Image Recognition

https://github.com/bethgelab/InDomainGeneralizationBenchmark

Deep Residual Learning for Image Recognition

https://github.com/better-chao/DSN

Domain Separation Networks

https://github.com/blablabananarama/ukiyoGAN

AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows

https://github.com/bobvo23/DANN-Plant-Counting

Unsupervised Domain Adaptation For Plant Organ Counting

https://github.com/boris127/vehicle-detection

Deep Residual Learning for Image Recognition

https://github.com/brycexu/MR-Residual-Net

Deep Residual Learning for Image Recognition

https://github.com/c1ph3rr/Deep-Residual-Learning-for-Image-Recognition

Deep Residual Learning for Image Recognition

https://github.com/caiqi/mean-teacher-cross-domain-detection

Exploring Object Relation in Mean Teacher for Cross-Domain Detection

https://github.com/calico/scnym

Domain-Adversarial Training of Neural Networks

https://github.com/calmisential/TensorFlow2.0_ResNet

Deep Residual Learning for Image Recognition

https://github.com/cameronchoi/r3det-copy

Deep Residual Learning for Image Recognition

https://github.com/canturan10/satellighte

Deep Residual Learning for Image Recognition

https://github.com/caojoshua/Plastic-Recyclability

Deep Residual Learning for Image Recognition

https://github.com/caoquanjie/ADDA-master

Adversarial Discriminative Domain Adaptation

https://github.com/cardwing/codes-for-pvkd

PolarMix: A General Data Augmentation Technique for LiDAR Point Clouds

https://github.com/carrenD/Med-CMDA

Unsupervised Cross-Modality Domain Adaptation of ConvNets for Biomedical Image Segmentations with Adversarial Loss

https://github.com/carrenD/Medical-Cross-Modality-Domain-Adaptation

Unsupervised Cross-Modality Domain Adaptation of ConvNets for Biomedical Image Segmentations with Adversarial Loss

https://github.com/casia-iva-lab/pass-reid

Person Transfer GAN to Bridge Domain Gap for Person Re-Identification

https://github.com/chayanchatterjee/cbc-skynet

Deep Residual Learning for Image Recognition

https://github.com/chayanchatterjee/gw-skylocator

Deep Residual Learning for Image Recognition

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.