Domain Adaptation

Domain Adaptation is the task of adapting models across domains. This is motivated by the challenge where the test and training datasets fall from different data distributions due to some factor. Domain adaptation aims to build machine learning models that can be generalized into a target domain and dealing with the discrepancy across domain distributions.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 2651–2675 of 6439 papers

Title	Date	Tasks	Status
Toward more accurate and generalizable brain deformation estimators for traumatic brain injury detection with unsupervised domain adaptation	Jun 8, 2023	Domain AdaptationUnsupervised Domain Adaptation	—Unverified
Unsupervised Cross-Domain Soft Sensor Modelling via Deep Physics-Inspired Particle Flow Bayes	Jun 8, 2023	Domain AdaptationMissing Labels	—Unverified
CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification	Jun 8, 2023	Contrastive LearningDomain Adaptation	—Unverified
Cross-Database and Cross-Channel ECG Arrhythmia Heartbeat Classification Based on Unsupervised Domain Adaptation	Jun 7, 2023	DiagnosticDomain Adaptation	—Unverified
Text-only Domain Adaptation using Unified Speech-Text Representation in Transducer	Jun 7, 2023	Domain AdaptationLanguage Modeling	—Unverified
Curriculum-Based Augmented Fourier Domain Adaptation for Robust Medical Image Segmentation	Jun 6, 2023	Domain AdaptationImage Segmentation	CodeCode Available
Real-Time Online Unsupervised Domain Adaptation for Real-World Person Re-identification	Jun 6, 2023	Domain AdaptationOnline unsupervised domain adaptation	—Unverified
Personalized Federated Domain Adaptation for Item-to-Item Recommendation	Jun 5, 2023	Domain AdaptationFederated Learning	—Unverified
Explaining and Adapting Graph Conditional Shift	Jun 5, 2023	Domain AdaptationGraph Classification	—Unverified
Generative Adversarial Networks for Data Augmentation	Jun 3, 2023	Data AugmentationDomain Adaptation	—Unverified
Is Generative Modeling-based Stylization Necessary for Domain Adaptation in Regression Tasks?	Jun 2, 2023	Domain AdaptationDomain Generalization	—Unverified
Federated Domain Generalization: A Survey	Jun 2, 2023	Domain AdaptationDomain Generalization	—Unverified
Text Style Transfer Back-Translation	Jun 2, 2023	Data AugmentationDomain Adaptation	CodeCode Available
GANs and alternative methods of synthetic noise generation for domain adaption of defect classification of Non-destructive ultrasonic testing	Jun 2, 2023	ClassificationDomain Adaptation	—Unverified
Neuronal Cell Type Classification using Deep Learning	Jun 1, 2023	ClassificationDeep Learning	—Unverified
Uneven Bi-Classifier Learning for Domain Adaptation	Jun 1, 2023	Domain AdaptationUnsupervised Domain Adaptation	CodeCode Available
Automatic Data Augmentation for Domain Adapted Fine-Tuning of Self-Supervised Speech Representations	Jun 1, 2023	Data AugmentationDomain Adaptation	—Unverified
FACT: Federated Adversarial Cross Training	Jun 1, 2023	Domain AdaptationFederated Learning	CodeCode Available
Topic-Guided Sampling For Data-Efficient Multi-Domain Stance Detection	Jun 1, 2023	Contrastive LearningDomain Adaptation	CodeCode Available
Maximal Domain Independent Representations Improve Transfer Learning	Jun 1, 2023	Domain AdaptationTransfer Learning	—Unverified
Hypothesis Transfer Learning with Surrogate Classification Losses: Generalization Bounds through Algorithmic Stability	May 31, 2023	Binary ClassificationClassification	—Unverified
Building Manufacturing Deep Learning Models with Minimal and Imbalanced Training Data Using Domain Adaptation and Data Augmentation	May 31, 2023	Data AugmentationDefect Detection	—Unverified
Deep into The Domain Shift: Transfer Learning through Dependence Regularization	May 31, 2023	Domain AdaptationTransfer Learning	CodeCode Available
Towards Flow Graph Prediction of Open-Domain Procedural Texts	May 31, 2023	ArticlesDomain Adaptation	—Unverified
Domain knowledge-informed Synthetic fault sample generation with Health Data Map for cross-domain Planetary Gearbox Fault Diagnosis	May 31, 2023	Domain AdaptationFault Diagnosis	—Unverified

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All datasets Office-31 SYNTHIA-to-Cityscapes GTA5 to Cityscapes Office-Home VisDA2017 ImageCLEF-DA Cityscapes to ACDC MNIST-to-USPS SVHN-to-MNIST USPS-to-MNIST SVNH-to-MNIST MoLane

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	FFTAT	Average Accuracy	96	—	Unverified
2	PMTrans	Average Accuracy	95.3	—	Unverified
3	CMKD	Average Accuracy	94.4	—	Unverified
4	SSRT-B (ours)	Average Accuracy	93.5	—	Unverified
5	CDTrans	Average Accuracy	92.6	—	Unverified
6	CoVi	Average Accuracy	91.8	—	Unverified
7	GSDE	Average Accuracy	91.7	—	Unverified
8	FixBi	Average Accuracy	91.4	—	Unverified
9	Contrastive Adaptation Network	Average Accuracy	90.6	—	Unverified
10	BIWAA	Average Accuracy	90.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HALO	mIoU	78.1	—	Unverified
2	ILM-ASSL	mIoU	76.6	—	Unverified
3	DCF	mIoU	69.3	—	Unverified
4	HRDA+PiPa	mIoU	68.2	—	Unverified
5	MIC	mIoU	67.3	—	Unverified
6	FREDOM - Transformer	mIoU	67	—	Unverified
7	HRDA	mIoU	65.8	—	Unverified
8	SePiCo	mIoU	64.3	—	Unverified
9	MIC + Guidance Training	mIoU	63.8	—	Unverified
10	DAFormer + ProCST	mIoU	61.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HALO	mIoU	77.8	—	Unverified
2	DCF	mIoU	77.7	—	Unverified
3	ILM-ASSL	mIoU	76.1	—	Unverified
4	MIC	mIoU	75.9	—	Unverified
5	HRDA+PiPa	mIoU	75.6	—	Unverified
6	HRDA	mIoU	73.8	—	Unverified
7	FREDOM - Transformer	mIoU	73.6	—	Unverified
8	HALO	mIoU	73.3	—	Unverified
9	SePiCo	mIoU	70.3	—	Unverified
10	DAFormer + ProCST	mIoU	69.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SWG	Accuracy	92.3	—	Unverified
2	RCL	Accuracy	90	—	Unverified
3	PGA (ViT-L/14)	Accuracy	89.4	—	Unverified
4	CMKD	Accuracy	89	—	Unverified
5	PMTrans	Accuracy	89	—	Unverified
6	MIC	Accuracy	86.2	—	Unverified
7	PGA (ViT-B/16)	Accuracy	85.1	—	Unverified
8	ELS	Accuracy	84.6	—	Unverified
9	SDAT (ViT-B/16)	Accuracy	84.3	—	Unverified
10	CDTrans (DeiT-B)	Accuracy	80.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FFTAT	Accuracy	93.8	—	Unverified
2	RCL	Accuracy	93.2	—	Unverified
3	MIC	Accuracy	92.8	—	Unverified
4	SWG	Accuracy	92.7	—	Unverified
5	CMKD	Accuracy	91.8	—	Unverified
6	DePT	Accuracy	90.7	—	Unverified
7	SDAT(ViT)	Accuracy	89.8	—	Unverified
8	SFDA2++	Accuracy	89.6	—	Unverified
9	PMtrans	Accuracy	88.8	—	Unverified
10	CoVi	Accuracy	88.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CMKD	Accuracy	94.3	—	Unverified
2	MCC+NWD	Accuracy	90.7	—	Unverified
3	GLOT-DR	Accuracy	90.4	—	Unverified
4	SPL	Accuracy	90.3	—	Unverified
5	DFA-SAFN	Accuracy	90.2	—	Unverified
6	DADA	Accuracy	89.3	—	Unverified
7	DFA-ENT	Accuracy	89.1	—	Unverified
8	DDA	Accuracy	88.9	—	Unverified
9	MEDM	Accuracy	88.9	—	Unverified
10	IAFN+ENT	Accuracy	88.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SoRA	mIoU	78.8	—	Unverified
2	Rein	mIoU	77.6	—	Unverified
3	CoDA	mIoU	72.6	—	Unverified
4	Refign (HRDA)	mIoU	72.1	—	Unverified
5	HALO	mIoU	71.9	—	Unverified
6	MIC	mIoU	70.4	—	Unverified
7	HRDA	mIoU	68	—	Unverified
8	Refign (DAFormer)	mIoU	65.5	—	Unverified
9	VBLC (DAFormer)	mIoU	64.2	—	Unverified
10	CMFormer	mIoU	60.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FACT	Accuracy	98.8	—	Unverified
2	FAMCD	Accuracy	98.72	—	Unverified
3	DFA-MCD	Accuracy	98.6	—	Unverified
4	Mean teacher	Accuracy	98.26	—	Unverified
5	DRANet	Accuracy	98.2	—	Unverified
6	SHOT	Accuracy	98	—	Unverified
7	DFA-ENT	Accuracy	97.9	—	Unverified
8	CyCleGAN (Light-weight Calibrator)	Accuracy	97.1	—	Unverified