Unsupervised Domain Adaptation

Also known as UDA

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16 papers in the last four weeks, up 78% on the four weeks before. 0.2% of all new papers.

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A Robust Unsupervised Domain Adaptation Framework for Medical Image Classification Using RKHS-MMD
May 5, 2026Sapna Sachan, Rakesh Kumar Sanodiya, Amulya Kumar MahtoChest X-Ray Classification Unsupervised Domain Adaptation
Mehta Family School of Data Science and Artificial Intelligence, Indian Institute of Technology Guwahati, India · Indian Institute of Information Technology, Design and Manufacturing,2026 Jabalpur, India
Orientation-Aware Unsupervised Domain Adaptation for Brain Tumor Classification Across Multi-Modal MRI
May 5, 2026Sapna Sachan, Amulya Kumar Mahto, Prashant Wagambar PatilUnsupervised Domain Adaptation Medical Image Classification
Indian Institute of Technology, Guwahati
SoDa2: Single-Stage Open-Set Domain Adaptation via Decoupled Alignment for Cross-Scene Hyperspectral Image Classification
May 5, 2026Yiwen Liu, Minghua Wang, Jing Yao +2Unsupervised Domain Adaptation Domain Adaptation
Institute of Robotics and Automatic Information System (IRAIS), College of Artificial Intelligence, and the Tianjin Key Laboratory of Intelligent Robotics (tjKLIR), Nankai University, Tianjin 300071, China · Aerospace Information Research Institute, Chinese Academy of Sciences, 100094 Beijing, China · Institute of Methodologies for Environmental Analysis (CNR-IMAA), National Research Council, 85050 Tito, Italy
Dual-Foundation Models for Unsupervised Domain Adaptation
May 5, 2026Yerin Cheon, Aruna Balasubramanian, Francois RameauSynthetic-to-Real Domain Adaptation Unsupervised Domain Adaptation
Stony Brook University, Stony Brook, NY, USA · SUNY Korea, The State University of New York, Korea
Multispectral Blind Image Super-Resolution for Standing Dead Tree Segmentation
May 4, 2026Mete Ahishali, Anis Ur Rahman, Einari Heinaro +2Remote Sensing Image Segmentation Unsupervised Domain Adaptation
Department of Forest Sciences, University of Helsinki, Finland · CSC – IT Center for Science Ltd., Espoo, Finland · KOKO Forest Ltd. +1
Heterogeneous Model Fusion for Privacy-Aware Multi-Camera Surveillance via Synthetic Domain Adaptation
May 4, 2026Peggy Joy Lu, Wei-Yu Chen, Yao-Tsung Huang +1Synthetic Data Augmentation Unsupervised Domain Adaptation
aDepartment of Computer Science and Information Engineering, National Chung Cheng2026 University, Chiayi, Taiwan · bDepartment of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan · cNational Center for High-Performance Computing, Taichung, Taiwan
WILD SAM: A Simulated-and-Real Data Augmentation for Autonomous Driving Perception under Challenging Weather
May 1, 2026Hamed Khatounabadi, Xiaohu Lu, Hayder RadhaSynthetic-to-Real Domain Adaptation Unsupervised Domain Adaptation
Electrical and Computer Engineering Michigan State University East Lansing, USA
Towards Robust Deep Learning-based Rumex Obtusifolius Detection from Drone Images
Apr 28, 2026Fabian Dionys Schrag, Mehmet Ozgur Turkoglu, Konrad Schindler +1Unsupervised Domain Adaptation Agricultural Remote Sensing
Agroscope NBA, Tänikon 1, Ettenhausen, 8356, TG, Switzerland · Agroscope Earth Observation of Agroecosystems Team, Reckenholz 191, Zurich, 8046, ZH, Switzerland · ETH Zurich, Stefano-Franscini-Platz 5, Zurich, 8093, ZH, Switzerland
UnIte: Uncertainty-based Iterative Document Sampling for Domain Adaptation in Information Retrieval
Apr 28, 2026Jongyoon Kim, Minseong Hwang, Seung-won HwangUnsupervised Domain Adaptation Domain Adaptation
Interdisciplinary Program in Artificial Intelligence, Seoul National University
Transfer Learning for Tonal Noise Prediction in VRF Units Using Thermodynamic and Vibration Signals
Apr 28, 2026ZhiWei Su, Ding Wang, Yuan Guo +2Unsupervised Domain Adaptation Transfer Learning
Corporate Research Center, Midea Group, Foshan528311, People’s Republic of China
A General Representation-Based Approach to Multi-Source Domain Adaptation
Apr 26, 2026Ignavier Ng, Yan Li, Zijian Li +3Multi-Source Domain Adaptation Unsupervised Domain Adaptation
Carnegie Mellon University · Mohamed bin Zayed University of Artificial Intelligence
Domain-Adapted Fine-Tuning of ECG Foundation Models for Multi-Label Structural Heart Disease Screening
Apr 25, 2026Duc N. Do, Minh N. Do, Dang Nguyen +14Unsupervised Domain Adaptation Echocardiography
1PASSIO Laboratory, North Carolina A&T State University, Greensboro, NC, USA · Department of Computer Science, University of Manitoba, Winnipeg, MB, Canada · 3Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA +4
PanDA: Unsupervised Domain Adaptation for Multimodal 3D Panoptic Segmentation in Autonomous Driving
Apr 21, 2026Yining Pan, Shijie Li, Yuchen Wu +2Unsupervised Domain Adaptation Multimodal Robustness
Singapore University of Technology and Design · Institute for Infocomm Research (I2R), A*STAR, Singapore
RoIt-XMASA: Multi-Domain Multilingual Sentiment Analysis Dataset for Romanian and Italian
Apr 18, 2026Andrei-Marius Avram, Aureliu Valentin Antonie, Cosmin-Mircea Croitoru +2Domain-Adversarial Learning Unsupervised Domain Adaptation
National University of Science and Technology POLITEHNICA Bucharest, Bucharest, Romania
Toward Robust Open-set Adaptation: Synapse Consolidation Inspired by Rac1/MAPK Pathways
Apr 1, 2026Xiao Zhang, Tianyu Hu, Juntao Lyu +2Test-Time Adaptation Unsupervised Domain Adaptation
School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, 100083, China. · Department of Automation, Tsinghua University, Beijing, 100084, China.
D-GAP: Improving Out-of-Domain Robustness via Dataset-Agnostic and Gradient-Guided Augmentation in Frequency and Pixel Spaces
Nov 14, 2025Ruoqi Wang, Haitao Wang, Shaojie Guo +1Unsupervised Domain Adaptation Data Augmentation
HKUST(GZ) · SYSU · ECNU +1
Multi-Channel Uncertainty-Weighted Score Matching for Conditional Diffusion in Medical UDA
Sep 26, 2025Chen Li, Meilong Xu, Xiaoling Hu +2Cross-Modality Medical Image Segmentation Unsupervised Domain Adaptation
Stony Brook University, Stony Brook, NY, USA · Massachusetts General Hospital and Harvard Medical School, MA, USA
Heterogeneous-Modal Unsupervised Domain Adaptation via Latent Space Bridging
Jun 19, 2025Jiawen Yang, Shuhao Chen, Shengtao Zhang +2Unsupervised Domain Adaptation Cross-Modal Alignment
Southern University of Science and Technology · SZ DJI Technology Co., Ltd
Freeze, Prompt, and Adapt: A Framework for Source-free Unsupervised GNN Prompting
May 22, 2025Peyman Baghershahi, Sourav MedyaSource-Free Domain Adaptation Unsupervised Domain Adaptation
Department of Computer Science University of Illinois Chicago
DIRA-SS:Dynamic Domain Incremental Regularised Adaptation -- Self-Supervised
Nov 13, 2023Abanoub Ghobrial, Kerstin EderTest-Time Adaptation Unsupervised Domain Adaptation
University of Bristol, Bristol, UK
DenseTRF: Texture-Aware Unsupervised Representation Adaptation for Surgical Scene Dense Prediction
Date pendingGuiqiu Liao, Matjaž Jogan, Daniel A. HashimotoUnsupervised Domain Adaptation Surgical Video Understanding
GRASP Laboratory, University of Pennsylvania · PCASO Laboratory, Department of Surgery, University of Pennsylvania · Department of Computer and Information Science, University of Pennsylvania

May 5, 2026, cs.CVJ/K move · Enter open · S save

A Robust Unsupervised Domain Adaptation Framework for Medical Image Classification Using RKHS-MMD

Sapna Sachan, Rakesh Kumar Sanodiya, Amulya Kumar Mahto

Mehta Family School of Data Science and Artificial Intelligence, Indian Institute of Technology Guwahati, India · Indian Institute of Information Technology, Design and Manufacturing,2026 Jabalpur, India

Chest X-Ray Classification Unsupervised Domain Adaptation Maximum Mean Discrepancy Medical Image Classification

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Labeling medical images is a major bottleneck in the field of medical imaging, as it requires domain-specific expertise, and it gets further complicated due to variability across different medical centers and different imaging devices. Such heterogeneity introduces domain shifts and modality discrepancies, which limits the generalization of trained models. To address this important challenge, we propose an unsupervised domain adaptation framework that combines transfer learning with a Reproducing Kernel Hilbert Space based Maximum Mean Discrepancy loss for the alignment of source and target domains. By jointly optimizing classification and RKHS-MMD losses, the methodology enhances generalization to unannotated medical datasets while diminishing reliance on manual annotation. Experimental evaluations presented on two chest X-ray datasets, which are obtained from different medical centers, show outstanding improvements over models trained without adaptation. Furthermore, we perform a comparative study to see that RKHS-MMD performs better than the standard Maximum Mean Discrepancy in reducing modality gap, emphasizing its effectiveness for medical image classification and also its strong capability in advanced AI-driven medical diagnostics.

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