Learning de-biased representations for remote-sensing imagery

Learning de-biased representations for remote-sensing imagery

Remote sensing (RS) imagery, requiring specialized satellites to collect and being difficult to annotate, suffers from data scarcity and class imbalance in certain spectrums. Due to data scarcity, training any large-scale RS models from scratch is unrealistic, and the alternative is to transfer pre-...

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Bibliographic Details
Main Authors: TIAN, Zichen, CHEN, Zhaozheng, SUN, Qianru
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2024
Subjects:
SAR
Remote-sensing images
LoRA
Visual transformers
Categorical Data Analysis
Databases and Information Systems
Online Access:https://ink.library.smu.edu.sg/sis_research/9400
https://ink.library.smu.edu.sg/context/sis_research/article/10400/viewcontent/2410.04546v1__1_.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/sis_research/9400
https://ink.library.smu.edu.sg/context/sis_research/article/10400/viewcontent/2410.04546v1__1_.pdf

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