REMP: A Unique Dataset of Rare and Endangered Medicinal Plants in Bangladesh

In Bangladesh, there are significant number of medicinal plants, but currently no comprehensive record of these valuable species is publicly available. Alarmingly, some of these plants are in a precarious state of endangerment. Therefore, we are creating a unique dataset of Bangladesh's rare, endangered, and threatened medicinal plants to support conservation efforts. It will help us to track and conserve endangered plant species, ensuring a more organized approach to research and preservation efforts. We conducted on-site visits to the National Botanical Garden and The Government Unani and Ayurvedic Medical College, capturing photographs of these plants in optimal sunlight conditions at various times of the day. This involved fieldwork, detailed image annotations, dataset organization, diversity augmentation, and contribution to the preservation of our natural heritage. We have collected a total of 16 types of rare and endangered medicinal plant leaf photos to create our unique dataset consisting of a total of 3494 images. This dataset will help researchers in biodiversity conservation through building efficient machine learning models and applying advanced machine learning techniques to identify rare and endangered medicinal plants.孟加拉国拥有大量药用植物，但目前尚无针对这些珍贵物种的公开全面记录。令人担忧的是，其中部分植物已处于濒危的脆弱境地。为此，我们构建了一套针对孟加拉国稀有、濒危和受威胁药用植物的专属数据集，以助力保护工作。本数据集可助力追踪与保护濒危植物物种，为研究与保护工作提供更系统化的路径。我们实地走访了国家植物园与政府优那尼-阿育吠陀医学院，在一日中不同时段的最佳光照条件下拍摄这些植物的照片。此项工作涵盖野外调研、精细化图像标注、数据集整理、样本多样性增强，以及助力保护自然遗产。我们共收集了16类稀有濒危药用植物的叶片照片，以此构建了包含3494张图像的专属数据集。本数据集将助力研究者通过构建高效机器学习模型、应用先进机器学习技术，实现对稀有濒危药用植物的识别，进而推动生物多样性保护工作。