repositories

GlobalGeoTree: A Multi-Granular Vision-Language Dataset for Global Tree Species Classification [ESSD 2026]

TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data

MPTSNet: Integrating Multiscale Periodic Local Patterns and Global Dependencies for Multivariate Time Series Classification [AAAI 2025]

Based on Google Earth remote sensing images of Wuhan in 2016, using pre-trained models Alexnet, VGG11, Resnet-50 and Resnet-101 for transfer learning, the classification model can predict the category of unknown remote sensing images with 90.48% accuracy (ResNet-101)