Detection and Management of Water Stress at Plants by Deep Learning and Image processing Case-study of Tomato
This project aims to develop an innovative technique for detecting water stress in tomato plants using deep learning and image processing techniques, and to integrate it into a mobile application for real-time monitoring. The methodology adopted includes the acquisition and preprocessing of image da...
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Format: | Article |
Language: | English |
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EDP Sciences
2025-01-01
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Series: | E3S Web of Conferences |
Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/01/e3sconf_icegc2024_00007.pdf |
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author | Guerbaoui Mohammed Ichou Ismail Bakziz Zakaria Selmani Abdelouahed El Faiz Samira Ed-Dahhak Abdelali Benhala Bachir Lachhab Abdeslam |
author_facet | Guerbaoui Mohammed Ichou Ismail Bakziz Zakaria Selmani Abdelouahed El Faiz Samira Ed-Dahhak Abdelali Benhala Bachir Lachhab Abdeslam |
author_sort | Guerbaoui Mohammed |
collection | DOAJ |
description | This project aims to develop an innovative technique for detecting water stress in tomato plants using deep learning and image processing techniques, and to integrate it into a mobile application for real-time monitoring. The methodology adopted includes the acquisition and preprocessing of image data, the construction and training of a deep learning model, and the development of a user-friendly mobile application. The results show a promising performance of the model in the precise detection of water stress, confirming the usefulness and usability of the developed mobile application. |
format | Article |
id | doaj-art-e887e86ae05043229a33ef33f434b28b |
institution | Kabale University |
issn | 2267-1242 |
language | English |
publishDate | 2025-01-01 |
publisher | EDP Sciences |
record_format | Article |
series | E3S Web of Conferences |
spelling | doaj-art-e887e86ae05043229a33ef33f434b28b2025-02-05T10:46:25ZengEDP SciencesE3S Web of Conferences2267-12422025-01-016010000710.1051/e3sconf/202560100007e3sconf_icegc2024_00007Detection and Management of Water Stress at Plants by Deep Learning and Image processing Case-study of TomatoGuerbaoui Mohammed0Ichou Ismail1Bakziz Zakaria2Selmani Abdelouahed3El Faiz Samira4Ed-Dahhak Abdelali5Benhala Bachir6Lachhab Abdeslam7MMCS Team, EST Meknes, Moulay Ismail UniversityFaculty of Sciences Meknes, Moulay Ismail UniversityFaculty of Sciences Meknes, Moulay Ismail UniversityS.A.R.S Team, ENSA of Safi, UCA UniversityMMCS Team, EST Meknes, Moulay Ismail UniversityMMCS Team, EST Meknes, Moulay Ismail UniversityFaculty of science Dhar El Mahraz, Sidi Mohamed Ben Abdellah UniversityMMCS Team, EST Meknes, Moulay Ismail UniversityThis project aims to develop an innovative technique for detecting water stress in tomato plants using deep learning and image processing techniques, and to integrate it into a mobile application for real-time monitoring. The methodology adopted includes the acquisition and preprocessing of image data, the construction and training of a deep learning model, and the development of a user-friendly mobile application. The results show a promising performance of the model in the precise detection of water stress, confirming the usefulness and usability of the developed mobile application.https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/01/e3sconf_icegc2024_00007.pdf |
spellingShingle | Guerbaoui Mohammed Ichou Ismail Bakziz Zakaria Selmani Abdelouahed El Faiz Samira Ed-Dahhak Abdelali Benhala Bachir Lachhab Abdeslam Detection and Management of Water Stress at Plants by Deep Learning and Image processing Case-study of Tomato E3S Web of Conferences |
title | Detection and Management of Water Stress at Plants by Deep Learning and Image processing Case-study of Tomato |
title_full | Detection and Management of Water Stress at Plants by Deep Learning and Image processing Case-study of Tomato |
title_fullStr | Detection and Management of Water Stress at Plants by Deep Learning and Image processing Case-study of Tomato |
title_full_unstemmed | Detection and Management of Water Stress at Plants by Deep Learning and Image processing Case-study of Tomato |
title_short | Detection and Management of Water Stress at Plants by Deep Learning and Image processing Case-study of Tomato |
title_sort | detection and management of water stress at plants by deep learning and image processing case study of tomato |
url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/01/e3sconf_icegc2024_00007.pdf |
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