Durian Plantation Epiphyte Lichen Image Dataset

Currently, the agriculture and forestry sectors face dual challenges of high productivity and ecological sustainability, with durian cultivation particularly reliant on refined environmental management. However, identifying epiphytic lichens on durian trees is a time-consuming task that requires specialized knowledge. Existing manual identification methods are inefficient and prone to significant errors. This dataset is dedicated to automating the identification of epiphytic lichens on durian trees through machine learning, reducing management costs and improving identification accuracy. The dataset is collected using high-resolution cameras in durian plantations, ensuring data richness from multiple angles and under different lighting conditions. Data quality control is performed using a combination of multiple rounds of annotation and machine learning validation, with the annotation team consisting of agricultural and biological experts to ensure professionalism and accuracy. The data undergoes preprocessing steps such as normalization, noise reduction, and augmentation, and is stored using a hierarchical folder structure for ease of access and management.