ManishSahu53 / Vector-Map-Generation-from-Aerial-Imagery-using-Deep-Learning-GeoSpatial-UNETLinks
We propose a simple yet efficient technique to leverage semantic segmentation model to extract and separate individual buildings in densely compacted areas using medium resolution satellite/UAV orthoimages. We adopted standard UNET architecture, additionally added batch normalization layer after every convolution, to label every pixel in the ima…
☆98Updated 3 years ago
Alternatives and similar repositories for Vector-Map-Generation-from-Aerial-Imagery-using-Deep-Learning-GeoSpatial-UNET
Users that are interested in Vector-Map-Generation-from-Aerial-Imagery-using-Deep-Learning-GeoSpatial-UNET are comparing it to the libraries listed below
Sorting:
- Regularization of Building Boundaries using Adversarial and Regularized losses☆144Updated 2 years ago
- Automated Building Detection using Deep Learning☆102Updated last year
- Road and Building Segmentation in Satellite Imagery☆144Updated 2 years ago
- Project to train/test convolutional neural networks to extract buildings from SpaceNet satellite imageries.☆202Updated 2 years ago
- Geoseg - A Computer Vision Package for Automatic Building Segmentation and Outline extraction☆113Updated 4 years ago
- A Semantic Segmentation Network for Urban-Scale Building Footprint Extraction Using RGB Satellite Imagery☆67Updated 2 years ago
- Urban change model designed to identify changes across 2 timestamps☆62Updated 2 years ago
- Using Pytorch implementation of U-Net architecture for road and building extraction☆132Updated 7 years ago
- Road network extraction from satellite imagery, with speed and travel time estimates☆197Updated 3 years ago
- Building footprint segmentation from satellite and aerial imagery☆163Updated last year
- Road network extraction from satellite imagery, with speed and travel time estimates☆69Updated 5 years ago
- The winning solutions for the SpaceNet 6 Challenge☆75Updated 5 years ago
- Label-Pixels is the tool for semantic segmentation of remote sensing images using Fully Convolutional Networks. Initially, it is designed…☆73Updated 3 years ago
- A sample project demonstrating how to extract building footprints from satellite images using a semantic segmentation model. Data from th…☆109Updated 5 years ago
- Open source notebooks to create state-of-the-art detection, segmentation, & classification of buildings on drone/aerial imagery with deep…☆196Updated 5 years ago
- Exploring the use of machine learning to convert a Digital Surface Model (e.g. SRTM) to a Digital Terrain Model☆72Updated 4 years ago
- Deep learning with otb (mirror of https://forgemia.inra.fr/orfeo-toolbox/otbtf)☆167Updated 7 months ago
- A curated list on building detection from remote sensing images☆87Updated 5 years ago
- The SpaceNet 7 Baseline Algorithm☆34Updated 5 years ago
- Winners of the Open Cities AI Challenge competition☆124Updated 2 years ago
- Super-Resolution Utilities for managing large satellite images☆16Updated 7 years ago
- Scripts to process aerial imagery☆33Updated 5 years ago
- Road Detection from satellite images using U-Net.☆59Updated last year
- PyTorch implementation for multi-task learning with aerial images for the datasets: IEEE Data Fusion Contest 2018 (DFC2018) and ISPRS-Va…☆84Updated 6 years ago
- Orthogonalize polygon in python by making all its angles 90 or 180 deg☆76Updated 4 years ago
- Python scripts for the textbook "Image Analysis, Classification and Change Detection in Remote Sensing, Fourth Revised Edition"☆110Updated 3 years ago
- List of labelled remote sensing datasets for use in deep learning.☆59Updated 8 years ago
- Training dataset for supervised learning☆59Updated 5 years ago
- ☆62Updated 4 years ago
- The presented experiment aims at using Pix2Pix network to segment the building footprint from Satellite Images.☆54Updated 5 years ago