Abschnitt: Artificial Intelligence Chapter 4: Geographical Applications | NFDI4Earth - Geospatial Intelligence for Sustainable Futures: Smart Data and AI Applications (WiSe 2024/25)

Abschnittsübersicht

In the Geographical Applications chapter, learners will apply AI techniques to real-world geospatial challenges. This includes ship detection using convolutional neural networks, weather prediction with recurrent neural networks, and modeling phenomena like water levels and soil sealing. By the end of this chapter, participants will have hands-on experience implementing AI-driven solutions for pressing geographic and environmental issues.
- Aktivität Artificial Neural Networks data auswählen
  
  Artificial Neural Networks data Datei
- Aktivität Hands-On Neural Networks: Classifying Soil Sealing with Sentinel-2 Data auswählen
  
  Hands-On Neural Networks: Classifying Soil Sealing with Sentinel-2 Data Interaktiver Inhalt
- Aktivität Neural Networks for Multiclass Classification: The Iris Dataset auswählen
  
  Neural Networks for Multiclass Classification: The Iris Dataset Interaktiver Inhalt
- Aktivität Convolutional Neural Networks data auswählen
  
  Convolutional Neural Networks data Datei
- Aktivität Introduction to Convolutional Neural Networks (CNNs): Theory and Applications auswählen
  
  Introduction to Convolutional Neural Networks (CNNs): Theory and Applications Interaktiver Inhalt
- Aktivität Building a CNN for Ship Detection in Radar Images auswählen
  
  Building a CNN for Ship Detection in Radar Images Interaktiver Inhalt
- Aktivität CNN for Ship Detection: Sliding Window Approach auswählen
  
  CNN for Ship Detection: Sliding Window Approach Interaktiver Inhalt
- Aktivität Introduction to Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTMs) auswählen
  
  Introduction to Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTMs) Interaktiver Inhalt
- Aktivität Weather Forecasting with LSTMs: Predicting Temperatures Using Time Series Data auswählen
  
  Weather Forecasting with LSTMs: Predicting Temperatures Using Time Series Data Interaktiver Inhalt