DeepOSM
Road classifier
Trains deep learning models to classify roads and features in satellite imagery using OpenStreetMap data.
Train a deep learning net with OpenStreetMap features and satellite imagery.
1k stars
87 watching
181 forks
Language: Python
last commit: almost 8 years ago
Linked from 4 awesome lists
Related projects:
Repository | Description | Stars |
---|---|---|
| Automating road detection from aerial imagery using deep learning techniques. | 541 |
| Automated object detection from aerial imagery using OpenStreetMap data and deep learning. | 192 |
| Automatically annotates satellite images with OpenStreetMap data | 461 |
| A deep learning framework for training highway networks on image data using convolutional neural networks | 57 |
| Developing deep learning models for Earth Observation using remote sensing images | 477 |
| A MATLAB implementation of a deep learning-based road boundary detection system using a pre-trained RESA model. | 3 |
| An image classification project applying deep neural networks to identify tree species from leaf images | 50 |
| Automates data preparation for machine learning with aerial imagery and OpenStreetMap data | 170 |
| Maintains a canonical list of commonly used features in OpenStreetMap to ensure consistent spelling and tagging. | 720 |
| Trains DeepLab model for semantic image segmentation using annotated data and various training procedures | 172 |
| PyTorch implementation of a deep learning model for image segmentation | 90 |
| A collection of tutorials and resources on implementing deep learning models using Python libraries such as Keras and Lasagne. | 426 |
| Tools for extracting street network data from OpenStreetMap | 59 |
| A deep learning-based object detection system from scratch | 706 |
| An image classification model using a third-generation deep residual network. | 27 |