From the 1 of 6 linked papers with an AI index.
6 papers
On the Disagreement in Perturbation-based xAI -- Benchmarking Perturbation Choices for Flood Detection from SAR Images
Anastasia Schlegel, Ronny Hänsch
The paper studies how different choices of patch size, shape, and replacement method in perturbation-based explainable AI affect the relevance maps for flood detection using SAR im…
Sentinel2Cap: A Human-Annotated Benchmark Dataset for Multimodal Remote Sensing Image Captioning
Lucrezia Tosato, Gianluca Lombardi, Ronny Hansch
Image captioning has become an important task in computer vision, enabling models to generate natural language descriptions of visual content. While several datasets exist for natu…
Data-Centric Benchmark for Label Noise Estimation and Ranking in Remote Sensing Binary Building Segmentation
Keiller Nogueira, Codrut-Andrei Diaconu, Dávid Kerekes +12
High-quality pixel-level annotations are essential for the semantic segmentation of remote sensing imagery. However, such labels are expensive to obtain and often affected by noise…
Very High-Resolution Forest Mapping with TanDEM-X InSAR Data and Self-Supervised Learning
José-Luis Bueso-Bello, Benjamin Chauvel, Daniel Carcereri +8
Deep learning models have shown encouraging capabilities for mapping accurately forests at medium resolution with TanDEM-X interferometric SAR data. Such models, as most of current…
Better Coherence, Better Height: Fusing Physical Models and Deep Learning for Forest Height Estimation from Interferometric SAR Data
Ragini Bal Mahesh, Ronny Hänsch
Estimating forest height from Synthetic Aperture Radar (SAR) images often relies on traditional physical models, which, while interpretable and data-efficient, can struggle with ge…
CerraData-4MM: A multimodal benchmark dataset on Cerrado for land use and land cover classification
Mateus de Souza Miranda, Ronny Hänsch, Valdivino Alexandre de Santiago Júnior +2
The Cerrado faces increasing environmental pressures, necessitating accurate land use and land cover (LULC) mapping despite challenges such as class imbalance and visually similar…