BDMediLeaves: A leaf images dataset for Bangladeshi medicinal plants identification

被引：9

作者：

Islam, Saiful ^{[1
]}

Ahmed, Md. Rayhan ^{[1
]}

Islam, Siful ^{[1
]}

Rishad, Md Mahfuzul Alam ^{[1
]}

Ahmed, Sayem ^{[1
]}

Utshow, Toyabur Rahman ^{[1
]}

Siam, Minhajul Islam ^{[1
]}

机构：

[1] United Int Univ, Dept Comp Sci & Engn, Madani Ave, Dhaka 1212, Bangladesh

来源：

DATA IN BRIEF | 2023年 / 50卷

关键词：

Medicinal leaf classification; Computer vision; Deep learning; Image processing;

D O I：

10.1016/j.dib.2023.109488

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：

This paper introduces a newly curated dataset named "BDMediLeaves" that includes a diverse collection of leaf images of ten distinct medicinal plants from various regions in Dhaka, Bangladesh. The ten distinct categories are Phyllanthus emblica, Terminalia arjuna, Kalanchoe pin-nata, Centella asiatica, Justicia adhatoda, Mikania micrantha, Azadirachta indica, Hibiscus rosasinensis, Ocimum tenuiflo-rum, and Calotropis gigantea. The dataset contains a total of 2,029 original leaf images, along with an additional 38,606 augmented images. Each original image was meticulously captured under natural lighting conditions with an appropriate background. Experts provided accurate labeling for each image, ensuring its seamless integration into various machine learning (ML) and deep learning (DL) models. This comprehensive dataset holds immense potential for researchers in utilizing various ML and DL methods to make significant advancements in the healthcare and pharmaceutical sectors. It serves as a valuable resource for future investigations, laying the foundation for crucial developments in these domains.

引用

页数：13

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