Nature's best vs. bruised: A veggie edibility evaluation databaseMendeley Data
In the realm of evaluating vegetable freshness, automated methods that assess external morphology, texture, and colour have emerged as efficient and cost-effective tools. These methods play a crucial role in sorting high-quality vegetables for both export and local consumption, significantly impacti...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-06-01
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| Series: | Data in Brief |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S235234092500215X |
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| author | Bidisha Samanta Sriparna Banerjee Ranadhir Das Sheli Sinha Chaudhuri Khalifa Djemal Amir Ali Feiz |
| author_facet | Bidisha Samanta Sriparna Banerjee Ranadhir Das Sheli Sinha Chaudhuri Khalifa Djemal Amir Ali Feiz |
| author_sort | Bidisha Samanta |
| collection | DOAJ |
| description | In the realm of evaluating vegetable freshness, automated methods that assess external morphology, texture, and colour have emerged as efficient and cost-effective tools. These methods play a crucial role in sorting high-quality vegetables for both export and local consumption, significantly impacting the revenue of the food industry worldwide. Researchers have recognized the importance of this area, leading to the development of various automated techniques, particularly leveraging advanced deep learning technologies to categorize vegetables into specific classes. However, the effectiveness of these methods heavily relies on the databases used for training and validation, posing a challenge due to the lack of suitable datasets. |
| format | Article |
| id | doaj-art-2fd753e07dac49698be14cac27b5aa62 |
| institution | OA Journals |
| issn | 2352-3409 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj-art-2fd753e07dac49698be14cac27b5aa622025-08-20T02:31:00ZengElsevierData in Brief2352-34092025-06-016011148310.1016/j.dib.2025.111483Nature's best vs. bruised: A veggie edibility evaluation databaseMendeley DataBidisha Samanta0Sriparna Banerjee1Ranadhir Das2Sheli Sinha Chaudhuri3Khalifa Djemal4Amir Ali Feiz5Electronics and Telecommunication Engineering Department, Jadavpur University, Kolkata, IndiaElectronics and Telecommunication Engineering Department, Jadavpur University, Kolkata, IndiaElectronics and Telecommunication Engineering Department, Jadavpur University, Kolkata, IndiaElectronics and Telecommunication Engineering Department, Jadavpur University, Kolkata, IndiaParis-Saclay University, Université d'Évry, IBISC, Evry, 91020, FranceParis-Saclay University, Université d'Évry, LMEE, Evry, 91020, France; Corresponding author.In the realm of evaluating vegetable freshness, automated methods that assess external morphology, texture, and colour have emerged as efficient and cost-effective tools. These methods play a crucial role in sorting high-quality vegetables for both export and local consumption, significantly impacting the revenue of the food industry worldwide. Researchers have recognized the importance of this area, leading to the development of various automated techniques, particularly leveraging advanced deep learning technologies to categorize vegetables into specific classes. However, the effectiveness of these methods heavily relies on the databases used for training and validation, posing a challenge due to the lack of suitable datasets.http://www.sciencedirect.com/science/article/pii/S235234092500215XAutomated vegetable edibility estimationDatabase comprising vegetables having varied edibilityComputer vision |
| spellingShingle | Bidisha Samanta Sriparna Banerjee Ranadhir Das Sheli Sinha Chaudhuri Khalifa Djemal Amir Ali Feiz Nature's best vs. bruised: A veggie edibility evaluation databaseMendeley Data Data in Brief Automated vegetable edibility estimation Database comprising vegetables having varied edibility Computer vision |
| title | Nature's best vs. bruised: A veggie edibility evaluation databaseMendeley Data |
| title_full | Nature's best vs. bruised: A veggie edibility evaluation databaseMendeley Data |
| title_fullStr | Nature's best vs. bruised: A veggie edibility evaluation databaseMendeley Data |
| title_full_unstemmed | Nature's best vs. bruised: A veggie edibility evaluation databaseMendeley Data |
| title_short | Nature's best vs. bruised: A veggie edibility evaluation databaseMendeley Data |
| title_sort | nature s best vs bruised a veggie edibility evaluation databasemendeley data |
| topic | Automated vegetable edibility estimation Database comprising vegetables having varied edibility Computer vision |
| url | http://www.sciencedirect.com/science/article/pii/S235234092500215X |
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