Building detection from the SpaceNet dataset by using Mask RCNN.
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Updated
Apr 1, 2021 - Jupyter Notebook
Building detection from the SpaceNet dataset by using Mask RCNN.
Building detection from the SpaceNet dataset using UNet.
Building detection model with YOLOv10 on UAVOD-10 dataset
This initiative leverages cutting-edge machine learning technique such as Mask R-CNN to automate the identification of buildings in satellite images after disasters. Employing high-resolution Maxar imagery, our models efficiently and accurately pinpoint affected structures, enhancing the speed and effectiveness of emergency responses.
Deep Learning Based Building Detection with Satellite Imagery
A deep learning project utilizing Mask R-CNN for building instance segmentation, openings detection, and building type classification.
This repository provides an implementation of semantic segmentation for road networks using PyTorch and the U-Net architecture. It focuses specifically on processing aerial images from the Massachusetts dataset.
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