Benchmarking Domain Adaptation Methods on Aerial Datasets

Benchmarking Domain Adaptation Methods on Aerial Datasets

Deep learning grew in importance in recent years due to its versatility and excellent performance on supervised classification tasks. A core assumption for such supervised approaches is that the training and testing data are drawn from the same underlying data distribution. This may not always be th...

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Bibliographic Details
Main Authors: Navya Nagananda, Abu Md Niamul Taufique, Raaga Madappa, Chowdhury Sadman Jahan, Breton Minnehan, Todd Rovito, Andreas Savakis
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Sensors
Subjects:
domain adaptation
aerial datasets
unsupervised learning
visualization
deep neural networks
Online Access:https://www.mdpi.com/1424-8220/21/23/8070

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https://www.mdpi.com/1424-8220/21/23/8070

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