NijatZeynalov / Satellite-images-to-real-maps-with-Deep-Learning
In this project, I developed a Pix2Pix generative adversarial network for image-to-image translation. I have used the so-called maps dataset used in the Pix2Pix paper.
☆27Updated 4 years ago
Alternatives and similar repositories for Satellite-images-to-real-maps-with-Deep-Learning:
Users that are interested in Satellite-images-to-real-maps-with-Deep-Learning are comparing it to the libraries listed below
- This repository is a complete walkthrough to download the "landcovernet" dataset that contains label masks for Sentinel 2 images from Afr…☆21Updated 4 years ago
- Road Detection from Remote Sensing Imagery using Deep Learning Techniques☆18Updated 2 years ago
- Using Deep Learning To Identify And Classify Building Damage☆15Updated 8 months ago
- Achieved a jaccard index of 0.75 with 100 images.LandCoverNet is a global annual land cover classification training dataset with labels f…☆11Updated 4 years ago
- Converting Aerial | Satellite images in RGB to the digital map using GAN (Pix2Pix).☆12Updated 4 years ago
- Slums detection through VHR and MR imagery☆14Updated 11 months ago
- Buildings segmentation from satellite imagery and damage classification for each build☆26Updated 6 years ago
- Land Cover Change Detection using Satellite Image Segmentation.☆50Updated 4 months ago
- List of datasets and codes for remote sensing LULC applications.☆44Updated 8 months ago
- Application of deep learning on Satellite Imagery of Sentinel-2 satellite that move around the earth from June, 2015. This image patches …☆89Updated last year
- Deep Learning Model For Water/Ice/Land Classification Using Large-Scale Medium Resolution Landsat Satellite Images☆14Updated 5 years ago
- ☆18Updated 2 years ago
- NGA Deep Learning☆27Updated 3 years ago
- Image segmentation models for building localization and damage assessment based on satellite imagery from the xBD dataset which was used …☆42Updated last year
- ☆19Updated 4 years ago
- Experimented with a U-Net variant to perform pixel wise multi-class classification to segment high resolution satellite imagery into land…