A Novel Deep Learning Model for Detection of Severity Level of the Disease in Citrus Fruits
<p dir="ltr">Citrus fruit diseases have an egregious impact on both the quality and quantity of the citrus fruit production and market. Automatic detection of severity is essential for the high-quality production of fruit. In the current work, a citrus fruit dataset is preprocessed b...
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| مؤلفون آخرون: | , , , , , |
| منشور في: |
2022
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| _version_ | 1864513506094612480 |
|---|---|
| author | Poonam Dhiman (12889038) |
| author2 | Vinay Kukreja (17054603) Poongodi Manoharan (17727687) Amandeep Kaur (572773) M. M. Kamruzzaman (19547827) Imed Ben Dhaou (17541504) Celestine Iwendi (18002485) |
| author2_role | author author author author author author |
| author_facet | Poonam Dhiman (12889038) Vinay Kukreja (17054603) Poongodi Manoharan (17727687) Amandeep Kaur (572773) M. M. Kamruzzaman (19547827) Imed Ben Dhaou (17541504) Celestine Iwendi (18002485) |
| author_role | author |
| dc.creator.none.fl_str_mv | Poonam Dhiman (12889038) Vinay Kukreja (17054603) Poongodi Manoharan (17727687) Amandeep Kaur (572773) M. M. Kamruzzaman (19547827) Imed Ben Dhaou (17541504) Celestine Iwendi (18002485) |
| dc.date.none.fl_str_mv | 2022-02-08T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.3390/electronics11030495 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/A_Novel_Deep_Learning_Model_for_Detection_of_Severity_Level_of_the_Disease_in_Citrus_Fruits/26947012 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Agricultural, veterinary and food sciences Agriculture, land and farm management Information and computing sciences Machine learning deep learning graph based segmentation object detection disease citrus fruits transfer learning severity |
| dc.title.none.fl_str_mv | A Novel Deep Learning Model for Detection of Severity Level of the Disease in Citrus Fruits |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Citrus fruit diseases have an egregious impact on both the quality and quantity of the citrus fruit production and market. Automatic detection of severity is essential for the high-quality production of fruit. In the current work, a citrus fruit dataset is preprocessed by rescaling and establishing bounding boxes with labeled image software. Then, a selective search, which combines the capabilities of both an extensive search and graph-based segmentation, is applied. The proposed deep neural network (DNN) model is trained to detect targeted areas of the disease with its severity level using citrus fruits that have been labeled with the help of a domain expert with four severity levels (high, medium, low and healthy) as ground truth. Transfer learning using VGGNet is applied to implement a multi-classification framework for each class of severity. The model predicts the low severity level with 99% accuracy, and the high severity level with 98% accuracy. The model demonstrates 96% accuracy in detecting healthy conditions and 97% accuracy in detecting medium severity levels. The result of the work shows that the proposed approach is valid, and it is efficient for detecting citrus fruit disease at four levels of severity.</p><h2>Other Information</h2><p dir="ltr">Published in: Electronics<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/electronics11030495" target="_blank">https://dx.doi.org/10.3390/electronics11030495</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_b77d6afcd3d2750dbbbf9721a624894c |
| identifier_str_mv | 10.3390/electronics11030495 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/26947012 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | A Novel Deep Learning Model for Detection of Severity Level of the Disease in Citrus FruitsPoonam Dhiman (12889038)Vinay Kukreja (17054603)Poongodi Manoharan (17727687)Amandeep Kaur (572773)M. M. Kamruzzaman (19547827)Imed Ben Dhaou (17541504)Celestine Iwendi (18002485)Agricultural, veterinary and food sciencesAgriculture, land and farm managementInformation and computing sciencesMachine learningdeep learninggraph based segmentationobject detectiondiseasecitrus fruitstransfer learningseverity<p dir="ltr">Citrus fruit diseases have an egregious impact on both the quality and quantity of the citrus fruit production and market. Automatic detection of severity is essential for the high-quality production of fruit. In the current work, a citrus fruit dataset is preprocessed by rescaling and establishing bounding boxes with labeled image software. Then, a selective search, which combines the capabilities of both an extensive search and graph-based segmentation, is applied. The proposed deep neural network (DNN) model is trained to detect targeted areas of the disease with its severity level using citrus fruits that have been labeled with the help of a domain expert with four severity levels (high, medium, low and healthy) as ground truth. Transfer learning using VGGNet is applied to implement a multi-classification framework for each class of severity. The model predicts the low severity level with 99% accuracy, and the high severity level with 98% accuracy. The model demonstrates 96% accuracy in detecting healthy conditions and 97% accuracy in detecting medium severity levels. The result of the work shows that the proposed approach is valid, and it is efficient for detecting citrus fruit disease at four levels of severity.</p><h2>Other Information</h2><p dir="ltr">Published in: Electronics<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/electronics11030495" target="_blank">https://dx.doi.org/10.3390/electronics11030495</a></p>2022-02-08T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.3390/electronics11030495https://figshare.com/articles/journal_contribution/A_Novel_Deep_Learning_Model_for_Detection_of_Severity_Level_of_the_Disease_in_Citrus_Fruits/26947012CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/269470122022-02-08T03:00:00Z |
| spellingShingle | A Novel Deep Learning Model for Detection of Severity Level of the Disease in Citrus Fruits Poonam Dhiman (12889038) Agricultural, veterinary and food sciences Agriculture, land and farm management Information and computing sciences Machine learning deep learning graph based segmentation object detection disease citrus fruits transfer learning severity |
| status_str | publishedVersion |
| title | A Novel Deep Learning Model for Detection of Severity Level of the Disease in Citrus Fruits |
| title_full | A Novel Deep Learning Model for Detection of Severity Level of the Disease in Citrus Fruits |
| title_fullStr | A Novel Deep Learning Model for Detection of Severity Level of the Disease in Citrus Fruits |
| title_full_unstemmed | A Novel Deep Learning Model for Detection of Severity Level of the Disease in Citrus Fruits |
| title_short | A Novel Deep Learning Model for Detection of Severity Level of the Disease in Citrus Fruits |
| title_sort | A Novel Deep Learning Model for Detection of Severity Level of the Disease in Citrus Fruits |
| topic | Agricultural, veterinary and food sciences Agriculture, land and farm management Information and computing sciences Machine learning deep learning graph based segmentation object detection disease citrus fruits transfer learning severity |