Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Techniques | 7,678 | 11 days ago | 2 | apache-2.0 | ||||||
Techniques for deep learning with satellite & aerial imagery | ||||||||||
Aitlas | 157 | 9 months ago | 2 | apache-2.0 | Python | |||||
AiTLAS implements state-of-the-art AI methods for exploratory and predictive analysis of satellite images. | ||||||||||
A2s2k Resnet | 132 | a year ago | 1 | Python | ||||||
A2S2K-ResNet: Attention-Based Adaptive Spectral-Spatial Kernel ResNet for Hyperspectral Image Classification | ||||||||||
Freenet | 99 | 6 months ago | 4 | gpl-3.0 | Python | |||||
FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification (TGRS 2020) https://ieeexplore.ieee.org/document/9007624 | ||||||||||
Hsi Traditional To Deep Models | 98 | 2 years ago | 3 | Jupyter Notebook | ||||||
Pytorch and Keras Implementations of Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects. | ||||||||||
Marta Gan | 66 | 6 years ago | 3 | mit | Python | |||||
MARTA GANs: Unsupervised Representation Learning for Remote Sensing Image Classification | ||||||||||
G2c Conv3d Hsi | 31 | 2 years ago | 1 | gpl-3.0 | Jupyter Notebook | |||||
PyTorch implementation of the paper - Revisiting Deep Hyperspectral Feature Extraction Networks via Gradient Centralized Convolution | ||||||||||
Polsarformer | 22 | 10 months ago | apache-2.0 | Jupyter Notebook | ||||||
This code is for the paper "Local Window Attention Transformer for Polarimetric SAR Image Classification" that is published in the IEEE Geoscience and Remote Sensing Letters journal. | ||||||||||
Ssun | 22 | 4 years ago | 5 | mit | Python | |||||
Spectral-Spatial Unified Networks for Hyperspectral Image Classification | ||||||||||
Remotior_sensus | 20 | 3 months ago | other | Python | ||||||
A Python package that allows for the processing of remote sensing images and GIS data. |