Building detection from the SpaceNet dataset by using Mask RCNN.

Packages intended to assist in the preprocessing of SpaceNet satellite imagery data corpus to a format that is consumable by machine learning algorithms.

Winning Solutions from SpaceNet Road Detection and Routing Challenge

Project to train/test convolutional neural networks to extract buildings from SpaceNet satellite imageries.

Building detector algorithms from second SpaceNet Challenge

python codes for remote sensing applications will be uploaded here. I will try to teach everything I learn during my projects in here.

This software is a modification of Visualizer from Spacenet competition for road extraction. I made it work for DeepGlobe dataset also.

Mask RCNN trained to detect buildings from the SpaceNet Off Nadir dataset

Building detection from the SpaceNet dataset using UNet.

Automatic Building Footprint Segmentation: U-Net Production-Level API

Tools for Implementation of STAC SPEC for SpaceNet dataset https://github.com/radiantearth/stac-spec/tree/dev

5th-place solution for SpaceNet-8: Flood Detection Challenge Using Multiclass Segmentation

Integrated Deep‑Learning Pipeline for Post‑Disaster Urban Damage Assessment

Group Project for USTH Deep Learning Course 2023, using Faster R-CNN with pretrained model weight (gone wrong)