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cs.CV2025★ 1 cited
ImageNet-trained CNNs are not biased towards texture: Revisiting feature reliance through controlled suppression
Tom Burgert, Oliver Stoll, Paolo Rota +1
The hypothesis that Convolutional Neural Networks (CNNs) are inherently texture-biased has shaped much of the discourse on feature use in deep learning. We revisit this hypothesis…
cs.CV2025
CSMoE: An Efficient Remote Sensing Foundation Model with Soft Mixture-of-Experts
Leonard Hackel, Tom Burgert, Begüm Demir
Self-supervised learning (SSL) through masked autoencoders (MAEs) has recently attracted great attention for remote sensing (RS) foundation model (FM) development, enabling improve…
cs.CV2025
On the Effectiveness of Methods and Metrics for Explainable AI in Remote Sensing Image Scene Classification
Jonas Klotz, Tom Burgert, Begüm Demir
The development of explainable artificial intelligence (xAI) methods for scene classification problems has attracted great attention in remote sensing (RS). Most xAI methods and th…