The overarching goal of ANTENNA is to fill key monitoring gaps through advancing innovative technologies that will underpin and complement EU-wide pollinator monitoring schemes, and to provide tested transnational pipelines from monitoring activities to curated datasets and enhanced indicators that support pollinator-relevant policy and end-users.
Our research group develop a comprehensive methodology for the identification and localization of flowers in orthoimages captured by UAVs. This approach involves testing and evaluating various image resolutions and convolutional neural network (CNN) models to optimize accuracy and efficiency. By leveraging advanced deep learning techniques, we aim to provide detailed descriptions of landscape that support pollinators, contributing to biodiversity conservation and ecosystem management.