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Galaxeye Eo Sar Change Detection

Lightweight multimodal EO--SAR change detection framework based on EfficientNet-B0 UNet architecture.

Fontehuggingface.co/juggtimber/galaxeye-eo-sar-change-detection/tree/f4ba9cddf33b4dac6508a23d6b25493480f458ad
TipoOtherModelo basegoogle/efficientnet-b0VersãoRevision f4ba9cdCnota

Fonte do modelo

Tipo
Other
Tamanho do arquivo
18,8–166 MB
Modelo base
google/efficientnet-b0
Versão
vRevision f4ba9cd
Atualizado
16 de set. de 2026
Downloads
0
Fonte
Hugging Face

Descrição da fonte

GalaxEye EO--SAR Change Detection

Lightweight multimodal EO--SAR change detection framework based on EfficientNet-B0 UNet architecture.

Overview

This model performs binary pixel-level change detection using paired Electro-Optical (EO) and Synthetic Aperture Radar (SAR) imagery.

The framework combines:

  • EO RGB channels
  • CLAHE-enhanced SAR
  • Log-transformed SAR

into a 5-channel multimodal segmentation input.

Architecture

  • EfficientNet-B0 encoder
  • UNet-style decoder
  • BCE + Dice + Focal hybrid loss

Results

SplitIoUF1
Validation0.27120.4267
Test0.08870.1629

Limitations

Performance degrades under cross-scene EO--SAR domain shift and heterogeneous SAR backscatter conditions.

Repository

GitHub repository: https://github.com/timbersaw-jugg/galaxeye-eo-sar-change-detection/

Fontes

1 fonte
Hugging FacePrimárioVersão f4ba9cddf33b4dac6508a23d6b25493480f458ad
huggingface.co/juggtimber/galaxeye-eo-sar-change-detection/tree/f4ba9cddf33b4dac6508a23d6b25493480f458ad

Verificado 1 de set.

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Artefatos de modelo

2 artefatos

efficientnet_b0/best_model.pth

pth · 18,8 MB · SHA-256 5e9efee42c26…e968 · Hugging Face

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resnet18/best_model.pth

pth · 166 MB · SHA-256 72d773480832…c1d1 · Hugging Face

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Trechos de fonte

2 trechos
Readme1 de set.huggingface.co/juggtimber/galaxeye-eo-sar-change-detection

--- license: mit language: - en base_model: - google/efficientnet-b0 pipeline_tag: image-segmentation tags: - remote_sensing, - change_detection - eo - segmentation - efficientnet --- # GalaxEye EO--SAR Change Detection Lightweight multimodal EO--SAR change detection framework based on EfficientNet-B0 UNet architecture. ## Overview This model performs binary pixel-level change detection using paired Electro-Optical (EO) and Synthetic Aperture Radar (SAR) imagery. The framework combines: - EO RGB channels - CLAHE-enhanced SAR - Log-transformed SAR into a 5-channel multimodal segmentation input. ## Architecture - EfficientNet-B0 encoder - UNet-style decoder - BCE + Dice + Focal hybrid loss ## Results | Split | IoU | F1 | |---|---|---| | Validation | 0.2712 | 0.4267 | | Test | 0.0887 | 0.1629 | ## Limitations Performance degrades under cross-scene EO--SAR domain shift and heterogeneous SAR backscatter conditions. ## Repository GitHub repository: https://github.com/timbersaw-jugg/galaxeye-eo-sar-change-detection/

Note1 de set.huggingface.co/juggtimber/galaxeye-eo-sar-change-detection

Source context: 0 downloads · 0 likes · Pipeline image-segmentation · Repo juggtimber/galaxeye-eo-sar-change-detection