Waternet
A convolutional neural network that identifies water in satellite images.
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Waternet | 202 | 7 years ago | 6 | mit | Python | |||||
| A convolutional neural network that identifies water in satellite images. | ||||||||||
| Delta | 169 | 2 years ago | 2 | apache-2.0 | Python | |||||
| Deep Learning for Satellite Imagery | ||||||||||
| Spacenet_building_detection | 140 | 10 months ago | 1 | mit | Jupyter Notebook | |||||
| Project to train/test convolutional neural networks to extract buildings from SpaceNet satellite imageries. | ||||||||||
| Urban Environments | 63 | 6 years ago | 2 | Jupyter Notebook | ||||||
| Code for constructing the urban environments dataset and for land use classification via convolutional neural networks | ||||||||||
| Temporalcnn | 59 | 4 years ago | gpl-3.0 | Python | ||||||
| Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series | ||||||||||
| Road Segmentation | 31 | 7 years ago | 2 | Jupyter Notebook | ||||||
| Satellite image segmentation (extraction of roads from satellite images) through convolutional neural networks (CNNs). | ||||||||||
| Deep Neural Network With Keras Python Satellite Image Classification | 20 | 6 years ago | 1 | Jupyter Notebook | ||||||
| Deep Neural Network with keras(TensorFlow GPU backend) Python: Satellite-Image Classification | ||||||||||
| Deephypercnn | 19 | 7 years ago | 3 | mit | Matlab | |||||
| Classification of Hyperspectral Satellite Image Using Deep Convolutional Neural Networks | ||||||||||
| Satellite Images Classification With Keras R | 12 | 6 years ago | R | |||||||
| Deep Neural Network with keras-R (TensorFlow GUP backend): Satellite-Image Classification | ||||||||||
| Pathlosspredictionsatelliteimages | 12 | 2 years ago | 15 | mit | Python | |||||
| Prediction of path loss using satellite images and convoluted neural networks | ||||||||||
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