78 citations · 130 across the 8 of their papers we have counts for
4 papers · 1 filter
Can Multitask Learning Enhance Model Explainability?
Hiba Najjar, Bushra Alshbib, Andreas Dengel
Remote sensing provides satellite data in diverse types and formats. The usage of multimodal learning networks exploits this diversity to improve model performance, except that the…
Unifying VXAI: A Systematic Review and Framework for the Evaluation of Explainable AI
David Dembinsky, Adriano Lucieri, Stanislav Frolov +3
Modern AI systems frequently rely on opaque black-box models, most notably Deep Neural Networks, whose performance stems from complex architectures with millions of learned paramet…
Data-Centric Machine Learning for Earth Observation: Necessary and Sufficient Features
Hiba Najjar, Marlon Nuske, Andreas Dengel
The availability of temporal geospatial data in multiple modalities has been extensively leveraged to enhance the performance of machine learning models. While efforts on the desig…
Explainability of Sub-Field Level Crop Yield Prediction using Remote Sensing
Hiba Najjar, Miro Miranda, Marlon Nuske +2
Crop yield forecasting plays a significant role in addressing growing concerns about food security and guiding decision-making for policymakers and farmers. When deep learning is e…