Data-centric AI approach for automated wildflower monitoring.

ABSTRACT: We present the Eindhoven Wildflower Dataset (EWD) as well as a PyTorch object detection model that is able to classify and count wildflowers. EWD, collected over two entire flowering seasons and expert annotated, contains 2,002 top-view images of flowering plants captured 'in the wild' in five different landscape types (roadsides, urban green spaces, cropland, weed-rich grassland, marshland). It holds a total of 65,571 annotations for 160 species belonging to 31 different families of flowering plants and serves as a reference dataset for automating wildflower monitoring and object detection in general. To ensure consistent annotations, we define species-specific floral count units and provide extensive annotation guidelines. With a 0.82 mAP (@IoU > 0.50) score the presented baseline model,

SUBMITTER: Schouten G 

PROVIDER: S-EPMC11383241 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature