Topic: "building-detection"
Mstfakts/Building-Detection-MaskRCNN
Building detection from the SpaceNet dataset by using Mask RCNN.
Language: Jupyter Notebook - Size: 16 MB - Last synced at: over 1 year ago - Pushed at: about 4 years ago - Stars: 191 - Forks: 20
Rim-chan/SpaceNet7-Buildings-Detection
Building detection from the SpaceNet dataset using UNet.
Language: Python - Size: 1.14 MB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 9 - Forks: 3
Picogeek06/FinalYear_Project
Deep Learning Based Building Detection with Satellite Imagery
Language: Jupyter Notebook - Size: 3.15 MB - Last synced at: about 2 years ago - Pushed at: almost 5 years ago - Stars: 4 - Forks: 1
dolphinium/uav-building-detection
Building detection model with YOLOv10 on UAVOD-10 dataset
Language: Python - Size: 114 MB - Last synced at: about 2 months ago - Pushed at: 2 months ago - Stars: 2 - Forks: 0
naayem/DeepLearning-BuildingSegmentation
A deep learning project utilizing Mask R-CNN for building instance segmentation, openings detection, and building type classification.
Language: Jupyter Notebook - Size: 191 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0
raphaelsulzer/PixelsPointsPolygons
The P3 dataset: Pixels, Points and Polygons for Multimodal Building Vectorization
Language: Python - Size: 18.3 MB - Last synced at: 14 days ago - Pushed at: 14 days ago - Stars: 0 - Forks: 0
Ruthik27/Building_Detection
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.
Language: Python - Size: 60.4 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0
MuhammedM294/AerialSeg
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.
Language: Jupyter Notebook - Size: 112 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0
