Segmenting satellite images of earth : determining which parts are roads.
-
Updated
Mar 26, 2017 - Python
Segmenting satellite images of earth : determining which parts are roads.
Road Extraction based on U-Net architecture (CVPR2018 DeepGlobe Challenge submission)
Pixel wise semantic segmentation for highway roads using FCN-8 architecture
Road Segmentation in Satellite Aerial Images
Road sementics segmentation using PSPU-NET
Road Segmentation.Image Segmentation using CNN Tensorflow with SegNet
Road Segmentation from Satelite images using custom Unet model
This repository is about my Final Project of my undergraduate course "Processamento Digital de Imagens" or Digital Image Processing, at UFABC.
SNE-RoadSeg for Freespace Detection in PyTorch, ECCV 2020
FCN implementation for road segmentation
Implementation of the paper "ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data" in TensorFlow.
Road segmentation using CNNs
Python scripts for performing road segemtnation and car detection using the HybridNets multitask model in ONNX.
Project for CS-433 Machine Learning @ EPFL
🎓 ML project for EPFL course CS-433 Machine Learning. Comparing ResNet and UNET for a road segmentation task.
Road Segmentation using Deep Learning
Code for the project "LinkNetB7: LinkNet with Pretrained Encoder for Efficient Road Segmentation"
Road segmentation in aerial images.
Combining Visual Transformers and U-shaped Networks for Road Segmentation
Training pipeline for deep neural networks for computer vision developed in Pytorch Lightning
Add a description, image, and links to the road-segmentation topic page so that developers can more easily learn about it.
To associate your repository with the road-segmentation topic, visit your repo's landing page and select "manage topics."