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Datasets/EuroSAT

EuroSAT

ImagesUnknownIntroduced 2017-08-31

Eurosat is a dataset and deep learning benchmark for land use and land cover classification. The dataset is based on Sentinel-2 satellite images covering 13 spectral bands and consisting out of 10 classes with in total 27,000 labeled and geo-referenced images.

Source: EuroSAT Image Source: EuroSAT

Benchmarks

Cross-Domain Few-Shot/5 shot Few-Shot Learning/Harmonic mean Few-Shot Learning/5 shot Image Classification/Accuracy (%)Image Clustering/Accuracy Meta-Learning/Harmonic mean Meta-Learning/5 shot Prompt Engineering/Harmonic mean Zero-Shot Learning/Accuracy

Related Benchmarks

EuroSAT 50 samples per class/Image Classification/Accuracy EuroSAT, 100 Labels/Image Classification/Percentage error EuroSAT, 100 Labels/Semi-Supervised Image Classification/Percentage error EuroSAT, 20 Labels/Image Classification/Percentage error EuroSAT, 20 Labels/Semi-Supervised Image Classification/Percentage error EuroSAT-SAR/Image Classification/Overall Accuracy

Statistics

Papers: 687
Benchmarks: 9

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Tasks

Classification Cross-Domain Few-Shot Few-Shot Learning Few-Shot Learning - 4 shots Image Classification Image Clustering Meta-Learning Prompt Engineering Semantic Segmentation Transductive Zero-Shot Classification Zero-Shot Learning