Convolutional Neural Networks for Texture Feature Extraction. Applications to Leaf Disease Classification in Precision Agriculture

Convolutional Neural Networks for Texture Feature Extraction. Applications to Leaf Disease Classification in Precision Agriculture

This paper studies the use of deep-learning models (AlexNet, VggNet, ResNet) pre-trained on object categories (ImageNet) in applied texture classification problems such as plant disease detection tasks. Research related to precision agriculture is of high relevance due to its potential economic impa...

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Bibliographic Details
Main Authors: Stefania Barburiceanu, Serban Meza, Bogdan Orza, Raul Malutan, Romulus Terebes
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Applied convolutional neural networks
leaf disease detection
image classification
texture classification
texture feature extraction
Online Access:https://ieeexplore.ieee.org/document/9627678/

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