Summary
- Year: 2022
- Total papers: 11
- Research papers hub
- All years
Topics
- Bee Behaviour (6)
- Computer Vision (5)
- Datasets Benchmarks (1)
- Edge AI Energy (1)
- IoT Sensors (5)
- Reviews Surveys (2)
- Robotics (2)
- Varroa Health (1)
Product areas
- Colony Health (1)
- Gate Tracker (2)
- Hive Scanner (1)
- Monitoring Platform (5)
- Robotics (2)
Papers by topic
Bee Behaviour
- A Minimally Invasive Approach Towards “Ecosystem Hacking” With Honeybees — 🇦🇹 University of Graz; 🇨🇿 Czech Technical University; 🇹🇷 Middle East Technical University
- Automated Video Monitoring of Unmarked and Marked Honey Bees at the Hive Entrance — 🇵🇷 University of Puerto Rico; 🇺🇸 Brown University; 🇺🇸 Howard Hughes Medical Institute (Janelia Research Campus)
- Bio-Hybrid Systems for Ecosystem Level Effects — 🇦🇹 University of Graz; 🇩🇪 Humboldt University of Berlin; 🇨🇭 École Polytechnique Fédérale de Lausanne; 🇩🇪 Freie Universität Berlin; 🇱🇻 Latvia University of Life Sciences and Technologies
- Evaluation of the honey bee colonies weight gain during theintensive foraging period — 🇱🇻 Latvia University of Life Sciences and Technologies
- Impact of the Precision Beekeeping on the Living Environment — 🇷🇸 University of Niš; 🇷🇸 Belgrade Metropolitan University
- SLEAP: A deep learning system for multi-animal pose tracking — 🇺🇸 Princeton University; 🇺🇸 New York University; 🇺🇸 Johns Hopkins University School of Medicine
Computer Vision
- Automated Video Monitoring of Unmarked and Marked Honey Bees at the Hive Entrance — 🇵🇷 University of Puerto Rico; 🇺🇸 Brown University; 🇺🇸 Howard Hughes Medical Institute (Janelia Research Campus)
- Deep Learning Beehive Monitoring System for Early Detection of the Varroa Mite — 🇬🇷 University of Ioannina
- Honeybee Re-identification in Video: New Datasets and Impact of Self-supervision — 🇵🇷 University of Puerto Rico
- Integration of Scales and Cameras in Nondisruptive ElectronicBeehive Monitoring: On the Within-Day Relationship of HiveWeight and Traffic in Honeybee (Apis mellifera) Colonies in Langstroth Hives in Tucson, Arizona, USA — 🇺🇸 Utah State University
- SLEAP: A deep learning system for multi-animal pose tracking — 🇺🇸 Princeton University; 🇺🇸 New York University; 🇺🇸 Johns Hopkins University School of Medicine
Datasets Benchmarks
- Honeybee Re-identification in Video: New Datasets and Impact of Self-supervision — 🇵🇷 University of Puerto Rico
Edge AI Energy
- Deep Learning Beehive Monitoring System for Early Detection of the Varroa Mite — 🇬🇷 University of Ioannina
IoT Sensors
- Digital Transformation of Beekeeping through the Use of a Decision Making Architecture — 🇫🇷 Efrei Research Lab; 🇫🇷 PSL University
- Evaluation of the honey bee colonies weight gain during theintensive foraging period — 🇱🇻 Latvia University of Life Sciences and Technologies
- Impact of the Precision Beekeeping on the Living Environment — 🇷🇸 University of Niš; 🇷🇸 Belgrade Metropolitan University
- Integration of Scales and Cameras in Nondisruptive ElectronicBeehive Monitoring: On the Within-Day Relationship of HiveWeight and Traffic in Honeybee (Apis mellifera) Colonies in Langstroth Hives in Tucson, Arizona, USA — 🇺🇸 Utah State University
- Smart Beehive Monitoring for Remote Regions - PhD thesis — 🇦🇺 University of Western Australia
Reviews Surveys
- Digital Transformation of Beekeeping through the Use of a Decision Making Architecture — 🇫🇷 Efrei Research Lab; 🇫🇷 PSL University
- Smart Beehive Monitoring for Remote Regions - PhD thesis — 🇦🇺 University of Western Australia
Robotics
- A Minimally Invasive Approach Towards “Ecosystem Hacking” With Honeybees — 🇦🇹 University of Graz; 🇨🇿 Czech Technical University; 🇹🇷 Middle East Technical University
- Bio-Hybrid Systems for Ecosystem Level Effects — 🇦🇹 University of Graz; 🇩🇪 Humboldt University of Berlin; 🇨🇭 École Polytechnique Fédérale de Lausanne; 🇩🇪 Freie Universität Berlin; 🇱🇻 Latvia University of Life Sciences and Technologies
Varroa Health
- Deep Learning Beehive Monitoring System for Early Detection of the Varroa Mite — 🇬🇷 University of Ioannina