Visual Diagnosis of the Varroa Destructor Parasitic Mite in Honeybees Using Object Detector Techniques

The Varroa destructor mite is one of the most dangerous Honey Bee (Apis mellifera) parasites worldwide and bee colonies have to be regularly monitored in order control its spread. In this paper we present an object detector based method for health state monitoring colonies. This has potential online measurement processing. our experiment, compare YOLO SSD detectors along with Deep SVDD anomaly detector. Based on custom dataset 600 ground-truth images healthy infected bees various scenes, reached highest F1 score up 0.874 detection 0.714 itself. results demonstrate approach, which will later used real-time computer vision honey inspection system. To best knowledge, study first using a bee. We expect that performance those enable us inspect status real time.