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Poster De Conférence Année : 2018

Automatic deforestation detection with deep learning: the case of Masoala National Park

Résumé

Large portions of territories are affected by deforestation. We aim to propose an approach based on convolutional neural networks to detect change in tropical forests. Our goal is to propose a model that requires minimal preprocessing and handcrafted features. We will test this approach with images from the Masoala National Park in Madagascar.

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Dates et versions

hal-02982957 , version 1 (06-11-2020)

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  • HAL Id : hal-02982957 , version 1

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Julius Akinyemi, Josiane Mothe, Nathalie Neptune. Automatic deforestation detection with deep learning: the case of Masoala National Park. 8th Advanced Training Course on Land Remote Sensing - ESALTC 2018, Sep 2018, Leicester, United Kingdom. , 521, 2018. ⟨hal-02982957⟩
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