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spatial-interpolation

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Source Codes for super resolution of the lunar elemental abundance map using a semi-supervised deep spatial interpolation model. This hybrid approach combined ResNet50 for spatial feature extraction with Graph Neural Network (GATv2Conv) layers and Convolutional Neural Networks (CNNs), followed by fusion layers.

  • Updated Feb 18, 2025
  • Python

Implementing a Python-based project using computer vision to analyse a wooden beer bottle cap display (shaped like Germany), aiming to correlate bottle caps with their geographic references by minimizing spatial distances between map holes and physical locations.

  • Updated Feb 12, 2024
  • Python

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