Article Dans Une Revue Data in Brief Année : 2025

Nature's best vs. bruised: A veggie edibility evaluation database

Résumé

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.

DOI

Documente 10.17632/b2mvj3kjfx.1 Jeu de données Banerjee, S. (2024). Nature’s Best vs. Bruised: A Veggie Evaluation [Data set]. Mendeley Data. https://doi.org/10.17632/B2MVJ3KJFX.1

Jeu de données présenté dans le data paper

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Bidisha Samanta, Sriparna Banerjee, Ranadhir Das, Sheli Sinha Chaudhuri, Khalifa Djemal, et al.. Nature's best vs. bruised: A veggie edibility evaluation database. Data in Brief, 2025, 60, pp.111483. ⟨10.1016/j.dib.2025.111483⟩. ⟨hal-05021853⟩
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