A Dataset of Malaysian Local Perennial Herbs for the Study of Plant Images Classification under Uncontrolled Environment.

The dataset of Malaysian local perennial herbs captured under uncontrolled environments provides a crucial resource for advancing plant image classification research in real-world conditions. By addressing the lack of publicly available image data for local herb species, it enables the development and benchmarking of robust machine learning models that can handle variations in lighting, backgrounds, and environmental noise. This has direct applications in creating AI-powered plant recognition tools for agriculture, biodiversity conservation, and the herbal industry, supporting accurate species identification, quality control, and sustainable harvesting practices. Furthermore, the dataset promotes the adoption of locally relevant AI solutions, enhancing precision agriculture and contributing to the preservation of Malaysia’s rich herbal biodiversity. Beyond research, it serves as an educational tool for students, researchers, and the public, fostering greater awareness and knowledge of Malaysia’s perennial herbs while driving innovation in agricultural technology and environmental monitoring.