Universal Domain Adaptation for Remote Sensing Image Scene Classification

01/26/2023
by   Qingsong Xu, et al.
0

The domain adaptation (DA) approaches available to date are usually not well suited for practical DA scenarios of remote sensing image classification, since these methods (such as unsupervised DA) rely on rich prior knowledge about the relationship between label sets of source and target domains, and source data are often not accessible due to privacy or confidentiality issues. To this end, we propose a practical universal domain adaptation setting for remote sensing image scene classification that requires no prior knowledge on the label sets. Furthermore, a novel universal domain adaptation method without source data is proposed for cases when the source data is unavailable. The architecture of the model is divided into two parts: the source data generation stage and the model adaptation stage. The first stage estimates the conditional distribution of source data from the pre-trained model using the knowledge of class-separability in the source domain and then synthesizes the source data. With this synthetic source data in hand, it becomes a universal DA task to classify a target sample correctly if it belongs to any category in the source label set, or mark it as “unknown" otherwise. In the second stage, a novel transferable weight that distinguishes the shared and private label sets in each domain promotes the adaptation in the automatically discovered shared label set and recognizes the “unknown” samples successfully. Empirical results show that the proposed model is effective and practical for remote sensing image scene classification, regardless of whether the source data is available or not. The code is available at https://github.com/zhu-xlab/UniDA.

READ FULL TEXT

page 1

page 3

page 7

page 9

research
04/09/2020

Universal Source-Free Domain Adaptation

There is a strong incentive to develop versatile learning techniques tha...
research
04/15/2021

Recent Advances in Domain Adaptation for the Classification of Remote Sensing Data

The success of supervised classification of remotely sensed images acqui...
research
01/19/2011

Classification under Data Contamination with Application to Remote Sensing Image Mis-registration

This work is motivated by the problem of image mis-registration in remot...
research
07/02/2022

Domain-Adaptive 3D Medical Image Synthesis: An Efficient Unsupervised Approach

Medical image synthesis has attracted increasing attention because it co...
research
05/17/2023

Integrating Multiple Sources Knowledge for Class Asymmetry Domain Adaptation Segmentation of Remote Sensing Images

In the existing unsupervised domain adaptation (UDA) methods for remote ...
research
12/03/2020

Deep Domain Adaptation based Cloud Type Detection using Active and Passive Satellite Data

Domain adaptation techniques have been developed to handle data from mul...
research
03/04/2022

Feature Transformation for Cross-domain Few-shot Remote Sensing Scene Classification

Effectively classifying remote sensing scenes is still a challenge due t...

Please sign up or login with your details

Forgot password? Click here to reset