Recognizing protected and anthropogenic patterns in landscapes using interpretable machine learning and satellite imagery
The accurate and comprehensive mapping of land cover has become a central task in
modern environmental research, with increasing emphasis on machine learning …
modern environmental research, with increasing emphasis on machine learning …
Leveraging activation maximization and generative adversarial training to recognize and explain patterns in natural areas in satellite imagery
A Emam, TT Stomberg… - IEEE Geoscience and …, 2023 - ieeexplore.ieee.org
Natural protected areas are vital for biodiversity, climate change mitigation, and supporting
ecological processes. Despite their significance, comprehensive mapping is hindered by a …
ecological processes. Despite their significance, comprehensive mapping is hindered by a …
MapInWild: A remote sensing dataset to address the question of what makes nature wild [Software and Data Sets]
The advancement in deep learning (DL) techniques has led to a notable increase in the
number and size of annotated datasets in a variety of domains, with remote sensing (RS) …
number and size of annotated datasets in a variety of domains, with remote sensing (RS) …
Confident Naturalness Explanation (CNE): A Framework to Explain and Assess Patterns Forming Naturalness
Protected natural areas characterized by minimal modern human footprint are often
challenging to assess. Machine-learning (ML) models, particularly explainable methods …
challenging to assess. Machine-learning (ML) models, particularly explainable methods …
MapInWild: A Remote Sensing Dataset to Address the Question What Makes Nature Wild
Antrophonegic pressure (ie human influence) on the environment is one of the largest
causes of the loss of biological diversity. Wilderness areas, in contrast, are home to …
causes of the loss of biological diversity. Wilderness areas, in contrast, are home to …
A regression-based Convolutional Neural Network for yield estimation of soybean
A Venugopal - 2023 - essay.utwente.nl
Crop yield estimation is essential for decision-making and ensuring food security. This MSc
thesis explores the explainability of a regression-based Convolutional Neural Network …
thesis explores the explainability of a regression-based Convolutional Neural Network …
Transformer-Based Reliable Explainability (T-ReX): A Framework to Reliably Interpret Naturalness using Foundation Models
T-ReX Poster Page 1 Transformer-Based Reliable Explainability (T-ReX): A Framework to
Reliably Interpret Naturalness using Foundation Models Motivation Method We propose the …
Reliably Interpret Naturalness using Foundation Models Motivation Method We propose the …