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https://github.com/lucashoeft/intelligent-data-analysis-2-project

Multiclass image classification of the EuroSAT satellite image dataset with convolutional neural network (CNN) and a pre-trained residual network (ResNet50) using transfer learning
https://github.com/lucashoeft/intelligent-data-analysis-2-project

cnn eurosat keras resnet sklearn tensorflow

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Multiclass image classification of the EuroSAT satellite image dataset with convolutional neural network (CNN) and a pre-trained residual network (ResNet50) using transfer learning

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# Intelligent-Data-Analysis-2-Project

The final project for the course 'Intelligent Data Analysis & Machine Learning II' at the University of Potsdam. The given task was to apply learned methods from the course on a self-chosen data set from kaggle. I chose a data set of Sentinel-2 satellite imagery of 10 classes with a total of 27k labeled images. The goal was to predict the right class labels for the given input images.

For prediction of the classes, I used a simple and an advanced convolutional neural network (CNN) and the ResNet50 with transfer learning. As a result the pre-trained ResNet50 outperforms all other models by far.

## Dataset

EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification (Vol. 12, Number 7, pp. 2217–2226). Zenodo. [https://doi.org/10.5281/zenodo.7711810](https://doi.org/10.5281/zenodo.7711810)