[HTML][HTML] Advancing arctic sea ice remote sensing with ai and deep learning: opportunities and challenges
Revolutionary advances in artificial intelligence (AI) in the past decade have brought
transformative innovation across science and engineering disciplines. In the field of Arctic …
transformative innovation across science and engineering disciplines. In the field of Arctic …
GeoAI for Science and the Science of GeoAI
This paper reviews trends in GeoAI research and discusses cutting-edge advances in GeoAI
and its roles in accelerating environmental and social sciences. It addresses ongoing …
and its roles in accelerating environmental and social sciences. It addresses ongoing …
Geospatial foundation models for image analysis: Evaluating and enhancing NASA-IBM Prithvi's domain adaptability
Research on geospatial foundation models (GFMs) has become a trending topic in
geospatial artificial intelligence (AI) research due to their potential for achieving high …
geospatial artificial intelligence (AI) research due to their potential for achieving high …
Improving interpretability of deep active learning for flood inundation map** through class ambiguity indices using multi-spectral satellite imagery
Flood inundation map** is a critical task for responding to the increasing risk of flooding
linked to global warming. Significant advancements of deep learning in recent years have …
linked to global warming. Significant advancements of deep learning in recent years have …
A taxonomy of multi-layered runtime guardrails for designing foundation model-based agents: Swiss cheese model for ai safety by design
Foundation Model (FM) based agents are revolutionizing application development across
various domains. However, their rapidly growing capabilities and autonomy have raised …
various domains. However, their rapidly growing capabilities and autonomy have raised …
A feature fusion method on landslide identification in remote sensing with Segment Anything Model
C Yang, Y Zhu, J Zhang, X Wei, H Zhu, Z Zhu - Landslides, 2025 - Springer
Utilizing remote sensing and deep learning methods can greatly enhance efficiency and
accuracy in landslide identification. However, the presence of vegetation cover and human …
accuracy in landslide identification. However, the presence of vegetation cover and human …
[HTML][HTML] Evaluating war-induced damage to agricultural land in the Gaza Strip since October 2023 using PlanetScope and SkySat imagery
Abstract The ongoing 2023 Israel-Hamas War has severe and far-reaching consequences
for the people, economy, food security, and environment. The immediate impacts of damage …
for the people, economy, food security, and environment. The immediate impacts of damage …
Adapting the Segment Anything Model for Volumetric X-ray Data-Sets of Arbitrary Sizes
R Gruber, S Rüger, T Wittenberg - Applied Sciences, 2024 - mdpi.com
We propose a new approach for volumetric instance segmentation in X-ray Computed
Tomography (CT) data for Non-Destructive Testing (NDT) by combining the Segment …
Tomography (CT) data for Non-Destructive Testing (NDT) by combining the Segment …
Segment Anything Model for Scan-to-Structural Analysis in Cultural Heritage
Segment anything model (SAM) proposed by META Artificial Intelligence (AI) has disrupted
the space of Deep Learning (DL) and Machine Learning (ML) and claims performance that …
the space of Deep Learning (DL) and Machine Learning (ML) and claims performance that …
A Novel Approach for Leveraging Agent-Based Experts on Large Language Models to Enable Data Sharing Among Heterogeneous IoT Devices in Agriculture
The rapid adoption of Internet of Things (IoT) devices in agriculture has led to the generation
of diverse data types, creating challenges in data sharing and integration across …
of diverse data types, creating challenges in data sharing and integration across …