noisy-labels-in-rs.org - Noisy Labels in Remote Sensing

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Description: Noisy Labels in Remote Sensing

learning (5660) image (3311) earth (1606) remote (1234) labels (1119) deep (589) classification (168) sensing (74) noisy (25) bigearth (1)

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Deep learning (DL) based methods have recently seen a rise in popularity in the context of remote sensing (RS) image classification. Most DL models require huge amounts of annotated images during training to optimize all parameters and reach a high-performance during evaluation. The availability and quality of such data determine the feasibility of many DL models. However, annotating RS images with multi-labels at large-scale to drive DL studies is time consuming, complex, and costly in operational scenario

We have recently started to research and develop noise robust DL models to reduce the negative impact of noisy land-use and land-cover annotations at the Remote Sensing Image Analysis (RSiM) group, TU Berlin .

RS-IRL-SVAE: Label Noise Robust Image Representation Learning based on Supervised Variational Autoencoders in Remote Sensing

Links to noisy-labels-in-rs.org (1)

• begumdemir.com Begüm Demir's web page