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- Ключ темы:
computer-vision - Всего статей: 55
- Центр исследовательских статей
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Продуктовые области
- Здоровье колонии (10)
- Gate Tracker (23)
- Hive Scanner (16)
- Платформа мониторинга (10)
- Робототехника (2)
Годы
Статьи по годам
2026
- Continuous Non-Invasive Monitoring of Hive Entrance Activity Reveals Honey Bee Colony Dynamics — 🇹🇷 Van Yüzüncü Yıl University
- M3DANet: A Lightweight Semi-Supervised Network and Embedded System for Bee Colony Counting — 🇨🇳 Shandong Agricultural University; 🇨🇳 Apiculture Institute of Jiangxi Province
2025
- An AI-Based Digital Scanner for Varroa destructor Detection in Beekeeping — 🇮🇹 Council for Agricultural Research and Economics (CREA) – Research Centre for Engineering and Agro-Food Processing, Monterotondo; 🇮🇹 Council for Agricultural Research and Economics (CREA) – Research Centre for Agriculture and Environment, Bologna; 🇷🇸 University of Novi Sad
- An AI-Based Open-Source Software for Varroa Mite Fall Analysis in Honeybee Colonies — 🇪🇸 University of Zaragoza; 🇪🇸 University of La Rioja; 🇪🇸 University of Valencia
- Apis mellifera Bee Verification with IoT and Graph Neural Network — 🇲🇽 Instituto Tecnológico El Llano Aguascalientes
- Deep Learning-Based Detection of Honey Storage Areas in Apismellifera Colonies for Predicting Physical Parameters of Honey via Linear Regression — 🇹🇭 Chiang Mai University
- Evaluation of Single-Shot Object Detection Models for Identifying Fanning Behavior in Honeybees at the Hive Entrance — 🇱🇹 Vilnius Gediminas Technical University
- Fast, accurate measurement of the worker populations of honey bee colonies using deep learning — 🇺🇸 Arizona State University; 🇺🇸 Texas A&M University–Kingsville
- Towards Varroa destructor mite detection using a narrow spectra illumination — 🇨🇿 Brno University of Technology
2024
- Autonomous tracking of honey bee behaviors over long-term periods with cooperating robots — 🇨🇿 Czech Technical University; 🇦🇹 University of Graz; 🇬🇧 Durham University; 🇹🇷 Middle East Technical University
- Beehive Smart Detector Device for the Detection of CriticalConditions That Utilize Edge Device Computations and DeepLearning Inferences — 🇬🇷 University of Ioannina
- IntelliBeeHive: An Automated Honey Bee, Pollen, and Varroa Destructor Monitoring System — 🇺🇸 University of Texas Rio Grande Valley
- Intelligent beehive monitoring system based on internet of things and colony state analysis — 🇲🇾 Universiti Teknologi MARA; 🇨🇳 Peking University Shenzhen Graduate School; 🇨🇳 Xiamen University; 🇨🇳 Fujian Agriculture And Forestry University; 🇨🇳 Quanzhou University of Information Engineering
- Keypoint-Based Bee Orientation Estimation and Ramp Detection at the Hive Entrance for Bee Behavior Identification System — 🇱🇹 Vilnius Gediminas Technical University
- Mapping Crop Types for Beekeepers Using Sentinel-2 Satellite Image Time Series: Five Essential Crops in the Pollination Services — 🇨🇦 Université de Montréal
- Towards Robotic Mapping of a Honeybee Comb — 🇨🇿 Czech Technical University; 🇬🇧 Durham University; 🇦🇹 University of Graz
- Varroa destructor detection on honey bees using hyperspectral imagery — 🇨🇿 Brno University of Technology; 🇫🇮 LUT University
2023
- Accuracy vs. Energy: An Assessment of Bee Object Inference inVideos from On-Hive Video Loggers with YOLOv3,YOLOv4-Tiny, and YOLOv7-Tiny — 🇺🇸 Utah State University
- Approximation of functions determining colony activity using neural networks. Master thesis — 🇨🇿 Brno University of Technology
- BeeNet: An End-To-End Deep Network For Bee Surveillance — 🇦🇺 Australian National University; 🇧🇩 BRAC University; 🇦🇺 Curtin University; 🇦🇺 Commonwealth Scientific and Industrial Research Organisation
- Detection of Varroa destructor Infestation of Honeybees Based on Segmentation and Object Detection Convolutional Neural Networks — 🇨🇳 Shandong Agriculture University
- Labeled dataset for bee detection and direction estimation on entrance to beehive — 🇱🇹 Vilnius Gediminas Technical University
- Machine Learning and Computer Vision Techniques in Continuous Beehive Monitoring Applications: A Survey — 🇨🇿 Brno University of Technology
- Pollinators as Data Collectors: Estimating Floral Diversity with Bees and Computer Vision — 🇩🇪 Karlsruhe Institute of Technology; 🇩🇪 apic.ai GmbH
- Precision Monitoring of Honey Bee (Hymenoptera: Apidae) Activity and Pollen Diversity during Pollination to EvaluateColony Health — 🇦🇺 La Trobe University
- Raspberry Pi Bee Health Monitoring Device — 🇨🇿 Brno University of Technology
- The Be-Hive Project - Counting Bee Traffic based on Deep Learning and Pose Estimation — 🇨🇾 CYENS Centre of Excellence; 🇨🇾 Cyprus University of Technology; 🇳🇱 University of Twente
- Varroa Destructor Classification Using Legendre Fourier Moments with Different Color Spaces — 🇲🇽 Universidad Politécnica de Tulancingo
2022
- 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
2021
- BeePIV: A Method to Measure Apis Mellifera Traffic with Particle Image Velocimetry in Videos — 🇺🇸 Utah State University
- DeepLabCut-based daily behavioural and posture analysis in a cricket — 🇯🇵 Waseda University
- Honeybee In-Out Monitoring System by Object Recognition and Tracking from Real-Time Webcams — 🇰🇷 Incheon National University
- Markerless tracking of an entire honey bee colony — 🇯🇵 Okinawa Institute of Science and Technology Graduate University; 🇦🇺 Australian National University; 🇳🇱 Vrije Universiteit Amsterdam
- On Image Classification in Video Analysis of Omnidirectional Apis Mellifera Traffic: Random Reinforced Forests vs. Shallow Convolutional Networks — 🇺🇸 Utah State University
- Visual Diagnosis of the Varroa Destructor Parasitic Mite in Honeybees Using Object Detector Techniques — 🇨🇿 Brno University of Technology
2020
- Automatic detection and classification of honey bee comb cells using deep learning — 🇵🇹 Instituto Politécnico de Bragança; 🇧🇷 Federal Technological University of Paraná; 🇫🇷 Université Clermont-Auvergne
- BeeAlarmed. Masters thesis — 🇩🇪 South Westphalia University of Applied Sciences
- Current achievements and future developments of a novel AI based visual monitoring of beehives in ecotoxicology and for the monitoring of landscape structures — 🇩🇪 apic.ai GmbH
- Real-time, low-latency closed-loop feedback using markerless posture tracking — 🇺🇸 Harvard University; 🇬🇧 NeuroGEARS Ltd; 🇺🇸 University of Oregon; 🇨🇭 Swiss Federal Institute of Technology
2019
- DeepBees – Building and Scaling Convolutional Neuronal Nets For Fast and Large-scale Visual Monitoring of Bee Hives — 🇩🇪 Karlsruhe Institute of Technology; 🇩🇪 apic.ai
- DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning — 🇩🇪 Max Planck Institute of Animal Behavior; 🇩🇪 University of Konstanz; 🇺🇸 Princeton University; 🇩🇪 Technische Universität München
- LabelBee: a web platform for large-scale semi-automated analysis of honeybee behavior from video — 🇵🇷 University of Puerto Rico
2018
- A Preliminary Study of Image Analysis forParasite Detection on Honey Bees — 🇦🇹 Vienna University of Technology; 🇪🇸 Universidad de Oviedo; 🇪🇸 Universitat de Barcelona
- DeepLabCut: markerless pose estimation of user-defined body parts with deep learning — 🇩🇪 Eberhard Karls Universität Tübingen; 🇺🇸 Harvard University; 🇺🇸 Columbia University; 🇩🇪 Max Planck Institute for Biological Cybernetics; 🇩🇪 Bernstein Center for Computational Neuroscience; 🇺🇸 Baylor College of Medicine
- Multiple Animals Tracking in VideoUsing Part Affinity Fields — 🇵🇷 University of Puerto Rico
- Recognition of Pollen-bearing Bees from Video using Convolutional Neural Network — 🇵🇷 University of Puerto Rico
- The development of honey bee coloniesassessed using a new semi-automated broodcounting method: CombCount — 🇦🇺 Macquarie University; 🇦🇺 Queensland University of Technology; 🇺🇸 Carl Hayden Bee Research Center
- Towards dense object tracking in a 2D honeybee hive — 🇯🇵 Okinawa Institute of Science and Technology Graduate University; 🇳🇱 VU University Amsterdam
- Tracking All Members of a Honey Bee Colony Over Their Lifetime Using Learned Models of Correspondence — 🇩🇪 Freie Universität Berlin; 🇩🇪 University of Konstanz; 🇩🇪 Robert Koch Institute; 🇺🇸 Auburn University; 🇺🇸 University of Hohenheim
2017
- Automatic detection and decoding of honey bee waggle dances — 🇩🇪 Freie Universität Berlin
2015
- Automatic methods for long-term tracking and the detection and decoding of communication dances in honeybees — 🇩🇪 Freie Universität Berlin; 🇬🇧 University of Sussex