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Deep Learning for Citrus Disease Detection by Andrés Alfonso Huanca Namuche is a document available to read on EtoBox.

What is Deep Learning for Citrus Disease Detection about?

This document discusses an image recognition method for identifying citrus diseases using deep learning. It proposes using the MobileNetV2 model to classify images of six common citrus diseases - including Huanglongbing, Anthracnose, Canker, Black spot, Sand paper rust, and Scabis. The method aims to reduce prediction time and model size compared to other networks, while maintaining classification accuracy. It trains the MobileNetV2 network on a dataset of citrus disease images and compares its performance

Author

Andrés Alfonso Huanca Namuche

Language

EN