Central India Medicinal Plant Dataset (CIMPD)Show others and affiliations
2025 (English)In: Data in Brief, E-ISSN 2352-3409, Vol. 63, article id 112154Article in journal (Refereed) Published
Abstract [en]
In the present scenario, medicinal plants play a crucial role in promoting a healthy lifestyle by protecting against numerous diseases. They also hold significant potential as a source of income, particularly for rural populations across the globe. Plants used for herbal medicine are known as medicinal plants, and each part of these plants may be utilized for medicinal purposes. Further, medicinal plants are beneficial in enhancing the human immune system. In this research, a new medicinal plant named as Central India Medicinal Plant Dataset (CIMPD) has been developed to support significant research in human health. The dataset contains 9130 leaf images (both healthy and unhealthy) from 23 medicinal plant species. These images were collected from various locations in central India. The entire work was carried out over a period of five months, which included plant selection, leaf collection, image capturing, and data organization into folders. This dataset provides comprehensive information, including the botanical name, common name, geographical origin, healthy and unhealthy leaf images, and medicinal uses of the plants. It serves as a valuable resource for research in machine learning, computer vision, and related domains. Additionally, it will enable the development and evaluation of methodologies for disease detection, plant identification, and other relevant applications.
Place, publisher, year, edition, pages
Elsevier BV , 2025. Vol. 63, article id 112154
Keywords [en]
Feature visualization, Image processing, Leaf images, Medicinal plant, Plant classification, ResNet18
National Category
Botany
Identifiers
URN: urn:nbn:se:kth:diva-372471DOI: 10.1016/j.dib.2025.112154ISI: 001598259100009PubMedID: 41140860Scopus ID: 2-s2.0-105019292114OAI: oai:DiVA.org:kth-372471DiVA, id: diva2:2012358
Note
QC 20251107
2025-11-072025-11-072025-11-07Bibliographically approved