A dataset revolutionizing Indian bay leaf analysis

被引：2

作者：

Paygude, Priyanka ^{[1
]}

Thite, Sandip ^{[2
]}

Kumar, Ajay ^{[3
]}

Bhosle, Amol ^{[4
]}

Pawar, Rajendra ^{[4
]}

Mane, Renuka ^{[5
]}

Joshi, Rahul ^{[6
]}

Kasar, Manisha ^{[1
]}

Chavan, Prashant ^{[1
]}

Gayakwad, Milind ^{[1
]}

机构：

[1] Bharati Vidyapeeth, Coll Engn, Pune, India

[2] Vishwakarma Univ, Pune, India

[3] Manipal Univ, Dept Comp Sci & Engn, Jaipur, India

[4] MIT Art Design & Technol Univ, MIT Sch Comp, Pune, India

[5] MIT World Peace Univ, Sch Comp Engn & Technol, Pune, India

[6] Symbiosis Int, Symbiosis Inst Technol, Pune, India

来源：

DATA IN BRIEF | 2024年 / 57卷

关键词：

Classification; Indian bay leaf dataset; Machine learning; Indian bay leaf quality assessment;

D O I：

10.1016/j.dib.2024.111024

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Indian bay leaf is a crucial spice in Indian cuisine. However, its quality and authenticity are often compromised. To address this, we introduce The Digital Indian Bay leaf dataset, a comprehensive collection of high-resolution 5696 images capturing diverse bay leaf samples under controlled conditions. The dataset encompasses variations in leaf conditions such as fresh leaf, dried leaf and diseased prone leaf. The dataset is meticulously curated to support research in condition analysis and machine learning applications for leaf quality assessment. To ensure data diversity, each category includes a wide range of images captured under controlled conditions with varying lighting, background, and leaf orientation. By providing a standardized and accessible resource, this dataset aims to accelerate research in this domain and contribute to the improvement of the Indian spice industry. (c) 2024 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC license ( http://creativecommons.org/licenses/by-nc/4.0/ )

引用

页数：7

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