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#

patchify

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Project to investigate and develop spatial data-driven Geo-AI models (Convolutional Neural Network) to identify urban greenspace from Satellite images by integrating multiple data sources (e.g. vector data of urban parks)

  • UpdatedFeb 26, 2023
  • Jupyter Notebook

Efficiently handles large images by segmenting them into patches, performing instance/semantic segmentation, and then reconstructing the patches into a complete, segmented mask.

  • UpdatedFeb 7, 2024
  • Jupyter Notebook

🛰️🌲Terra_Mask is an end-to-end computer vision project for semantic segmentation in land cover classification. It uses deep learning with PyTorch to classify features in high-resolution satellite imagery — such as buildings, woodland, water, and roads.

  • UpdatedOct 10, 2025
  • Jupyter Notebook

Repository for semantic segmentation of aerial imagery using U-Net, featuring training scripts, data preprocessing, and model evaluation.

  • UpdatedJun 18, 2024
  • Jupyter Notebook

Major Project CSE-563: "Image SuperResolution using Random Forest Regressor(RFSR), Support Vector Regressor(SVR) Machine learning Models."

  • UpdatedDec 15, 2024
  • Jupyter Notebook

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