Using a Novel Convolutional Neural Network for Plant Pests Detection and Disease Classification.

Wasswa ShafikAli TufailChandratilak De Silva LiyanageRosyzie Anna Awg Haji Mohd Apong

Published in: Journal of the science of food and agriculture (2023)

The presented model attained 99.2% accuracy in comparison to the cutting-edge models on different classifiers like LSTM, LR, and ELM, and performed better in comparison to transfer learning (TL). Pre-trained models, like VGG-19, VGG-18, and AlexNet, demonstrated better accuracy when the fc6 layer was compared to other layers. This article is protected by copyright. All rights reserved.

Keyphrases

convolutional neural network
deep learning
machine learning
resistance training
body composition
sensitive detection