Satellite images classification
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Updated
Nov 30, 2019 - Python
Satellite images classification
ANN to SNN conversion on land cover and land use classification problem for increased energy efficiency.
A fast and easy-to-use Remote sensing Image format COnverter for High-throughput Deep-Learning (rico-hdl).
Interactive web app for land use classification from Sentinel-2 satellite imagery using deep learning.
Federated Learning in Satellite Constellations using Flower
Multispectral satellite image classification on EuroSAT using Swin Transformer, Res2Net, and CSWin with SHAP explainability — Apache-2.0
Trained a ResNet50 model on the EuroSAT satellite imagery dataset w/ PyTorch. Analyzed the model's encoder by visualizing linear interpolations within the embedding space to illustrate the semantic separation in the learned feature representations.
A Geo-AI engine for automated ESG and supply chain monitoring. This project uses a ResNet-101 model, fine-tuned on the EuroSAT satellite dataset, to classify land use and detect environmental risks like deforestation, helping enterprises meet regulatory requirements and enhance transparency.
A comparative analysis of state-of-the-art CNN and transformer architectures for an image classification problem.
Residual Network implementation for classifying satellite images from EuroSAT dataset
Trabalho da disciplina de Sensoriamento Remoto (GEO05038) de 2022/1
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