CNN Features for Remote Sensing Image Classification

Tools and resources for remote sensing image classification using convolutional neural networks (convnets).

Collection SAT CNN Models contains code and pretrained convnet models for classification of satellite images. The convnets are trained on publicly available SAT-4 and SAT-6 datasets of satellite images (http://csc.lsu.edu/~saikat/deepsat/). The collection contains the following datasets:
SAT-4 Models - CNN models trained on SAT-4 dataset
SAT-6 Models - CNN models trained on SAT-6 dataset
Tools & Results - code for convnet training and image classification, conference paper and presentation.

Collection HRRS Image Classification contains code and pretrained convnet models for classification of high resolution remote sensing (HRRS) images. The convnets are trained/fine-tuned on publicly available AID dataset of HRRS images (http://captain.whu.edu.cn/project/AID/). The collection contains the following datasets:
Trained convnet models - models trained from scratch on AID dataset
Fine-tuned convnet models - models pretrained on ImageNet and fine-tuned on AID dataset
Tools & Results - code of an experimental framework for training and testing different convnet topologies for HRRS image classification, conference paper and presentation.

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HRRS Image Classification

Code and models for training convolutional neural networks (CNN) and satellite image classification using AID dataset (http://captain.whu.edu.cn/project/AID/).

Thumbnail of SAT CNN Models

SAT CNN Models

Code and models for training convolutional neural networks (CNN) and satellite image classification using SAT-4 and SAT-6 datasets (http://csc.lsu.edu/~saikat/deepsat/).

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