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LSTM-Based Discrimination of Date Fruit (Phoenix dactylifera L.) Based on Selected Convolutional Neural Network Features Cover

LSTM-Based Discrimination of Date Fruit (Phoenix dactylifera L.) Based on Selected Convolutional Neural Network Features

Acta Universitatis Cibiniensis. Series E: Food Technology
Volume 28 (2024): Issue 2 (December 2024)
By: Younés Noutfia,  Kadir Sabanci,  Muhammet Fatih Aslan and  Ewa Ropelewska  
Open Access
|Feb 2025

Authors

Younés Noutfia

younes.noutfia@inhort.pl

Fruit and Vegetable Storage and Processing Department, The National Institute of Horticultural Research, Skierniewice, Poland

Kadir Sabanci

Department of Electrical-Electronic Engineering, Karamanoglu Mehmetbey University, Karaman, Turkey

Muhammet Fatih Aslan

Department of Electrical-Electronic Engineering, Karamanoglu Mehmetbey University, Karaman, Turkey

Ewa Ropelewska

ewa.ropelewska@inhort.pl

Fruit and Vegetable Storage and Processing Department, The National Institute of Horticultural Research, Skierniewice, Poland
DOI: https://doi.org/10.2478/aucft-2024-0015 | Journal eISSN: 2344-150X | Journal ISSN: 2344-1496
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Language: English
Page range: 183 - 194
Submitted on: Sep 18, 2024
|
Accepted on: Dec 20, 2024
|
Published on: Feb 15, 2025
Published by: Lucian Blaga University of Sibiu
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year
Keywords:
Mejhoul,
date cultivar,
Classification,
Convolutional Neural Network,
Feature Selection,
Long short-term memory
Related subjects:
Industrial chemistry,
Industrial chemistry, other,
Food science and technology

© 2025 Younés Noutfia, Kadir Sabanci, Muhammet Fatih Aslan, Ewa Ropelewska, published by Lucian Blaga University of Sibiu
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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