Dataset of seven tropical flower species from Bangladesh: A resource for classification and ecological studies

We present the Tropical Flower Dataset: Seven Species from Bangladesh, a collection of 4,319 high-quality images containing seven tropical flower species: Rose (827), Bougainvillea (580), Marigold (717), Hibiscus (548), Crown of Thorn (583), Jungle Geranium (698), and Madagascar Periwinkle (366). All images were taken using a Redmi Note 11 smartphone at different locations within the Dhaka Division. The dataset is beneficial for flower classification and ecological purposes, encompassing diverse growth stages and distinct lighting conditions. Future work will focus on improving generalization through data augmentation and fine-tuning, aiming to enhance automated flower species recognition for ecological monitoring, biodiversity studies, and botany education.

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Publication Details

Journal
Data in Brief
Published
2025-02-07
DOI
https://doi.org/10.1016/j.dib.2025.111374
Citations
2
Primary Topic
Agricultural Economics and Practices
Type
article
Field-Weighted Citation Impact
9.66
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article

Dataset of seven tropical flower species from Bangladesh: A resource for classification and ecological studies

Narayan Ranjan Chakraborty, Mayen Uddin Mojumdar, Md. Shamim Hossain, Riazul Islam Rahat
2 citations
Data in Brief
Agricultural Economics and Practices
9.66
article

Dataset of seven tropical flower species from Bangladesh: A resource for classification and ecological studies

Narayan Ranjan Chakraborty, Mayen Uddin Mojumdar, Md. Shamim Hossain, Riazul Islam Rahat
article en
2 citations

Abstract

We present the Tropical Flower Dataset: Seven Species from Bangladesh, a collection of 4,319 high-quality images containing seven tropical flower species: Rose (827), Bougainvillea (580), Marigold (717), Hibiscus (548), Crown of Thorn (583), Jungle Geranium (698), and Madagascar Periwinkle (366). All images were taken using a Redmi Note 11 smartphone at different locations within the Dhaka Division. The dataset is beneficial for flower classification and ecological purposes, encompassing diverse growth stages and distinct lighting conditions. Future work will focus on improving generalization through data augmentation and fine-tuning, aiming to enhance automated flower species recognition for ecological monitoring, biodiversity studies, and botany education.

Data in BriefVol. 59
Daffodil International University (BD)
Life in Land
Openalex Percentile: Top 3%
Agricultural Economics and Practices
9.66
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