Evaluation of Deep Learning Models for Insects Detection at the Hive Entrance for a Bee Behavior Recognition System

Evaluation of Deep Learning Models for Insects Detection at the Hive Entrance for a Bee Behavior Recognition System

Monitoring insect activity at hive entrances is essential for advancing precision beekeeping practices by enabling non-invasive, real-time assessment of the colony’s health and early detection of potential threats. This study evaluates deep learning models for detecting worker bees, pollen-bearing b...

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Bibliographic Details
Main Authors: Gabriela Vdoviak, Tomyslav Sledevič, Artūras Serackis, Darius Plonis, Dalius Matuzevičius, Vytautas Abromavičius
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Agriculture
Subjects:
beehive monitoring
pollination surveillance
insect detection
convolutional neural networks
Jetson GPU
Online Access:https://www.mdpi.com/2077-0472/15/10/1019
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