Research graph
References from Bees and bytes: A systematic review of artificial intelligence in honey bee research (2011–2025). Local targets link to admitted publications; unresolved targets remain external evidence.
Automated beehive acoustics monitoring: A comprehensive review of the literature and recommendations for future work
10.3390/app12083920 · 2022 · External reference
A review on predicting bee honey production using machine learning
2024 · External reference
Review on machine learning models for efficient queen bee identification in beehives
2025 · External reference
Automatic detection and classification of honey bee comb cells using deep learning
10.1016/j.compag.2020.105244 · 2020 · External reference
IoT monitoring and prediction modeling of honeybee activity with alarm
10.3390/electronics11050783 · 2022 · External reference
Chronos: Learning the language of time series
2024 · External reference
Buzzing with intelligence: Current issues in apiculture and the role of artificial intelligence (AI) to tackle it
10.3390/insects15060418 · 2024 · External reference
A national survey of managed honey bee colony losses in the usa: Results from the bee informed partnership for 2020–21 and 2021–22
10.1080/00218839.2023.2264601 · 2023 · External reference
Pollen bearing honey bee detection in hive entrance video recorded by remote embedded system for pollination monitoring
2016 · External reference
Unresolved reference
2024 · External reference
A machine learning approach for queen bee detection through remote audio sensing to safeguard honeybee colonies
10.1109/tafe.2024.3406648 · 2024 · External reference
Automated identification of honey bee pollen loads for field-applied palynological studies
10.1111/nph.70435 · 2025 · External reference
Detection and tracking of honeybees using YOLO and StrongSORT
2022 · External reference
Artificial intelligence-driven tool for spectral analysis: identifying pesticide contamination in bees from reflectance profiling
10.1016/j.jhazmat.2024.136425 · 2024 · External reference
Ethoflow: Computer vision and artificial intelligence-based software for automatic behavior analysis
10.3390/s21093237 · 2021 · External reference
Artificial intelligence versus natural selection: Using computer vision techniques to classify bees and bee mimics
2022 · External reference
Machine learning and computer vision techniques in continuous beehive monitoring applications: A survey
10.1016/j.compag.2023.108560 · 2024 · External reference
A computer vision system to monitor the infestation level of Varroa destructor in a honeybee colony
10.1016/j.compag.2019.104898 · 2019 · External reference
Real-time insect tracking and monitoring with computer vision and deep learning
10.1002/rse2.245 · 2022 · External reference
Automated computer-based detection of encounter behaviours in groups of honeybees
10.1038/s41598-017-17863-4 · 2017 · External reference
Tracking all members of a honey bee colony over their lifetime using learned models of correspondence
10.3389/frobt.2018.00035 · 2018 · External reference
Towards dense object tracking in a 2D honeybee hive
2018 · External reference
Markerless tracking of an entire honey bee colony
10.1038/s41467-021-21769-1 · 2021 · External reference
An intelligent monitoring system for assessing bee hive health
10.1109/access.2021.3089538 · 2021 · External reference
Bee together: Joining bee audio datasets for hive extrapolation in AI-based monitoring
10.3390/s24186067 · 2024 · External reference
Image-based species identification of wild bees using convolutional neural networks
10.1016/j.ecoinf.2019.101017 · 2020 · External reference
Evaluation of classification performance of honey bee species with deep learning models
10.5152/electr.2025.24157 · 2025 · External reference
Honey bee piping detection utilizing convolutional neural networks
10.1109/jsen.2025.3531698 · 2025 · External reference
Detection of anomalies in bee colony using transitioning state and contrastive autoencoders
10.1016/j.compag.2022.107207 · 2022 · External reference
Honeybee re-identification in video: New datasets and impact of self-supervision
2022 · External reference
A machine learning-based multiclass classification model for bee colony anomaly identification using an IoT-based audio monitoring system with an edge computing framework
10.1016/j.eswa.2024.124898 · 2024 · External reference
An imaging system for monitoring the in-and-out activity of honey bees
10.1016/j.compag.2012.08.006 · 2012 · External reference
3D tracking of honeybees enhanced by environmental context
2013 · External reference
Detecting and tracking honeybees in 3D at the beehive entrance using stereo vision
10.1186/1687-5281-2013-59 · 2013 · External reference
Automated honey bee subspecies identification using advanced wing venation analysis and adaptive hierarchical clustering
10.1002/ece3.72101 · 2025 · External reference
Anomaly detection in beehives using deep recurrent autoencoders
2020 · External reference
Anomaly detection in beehives: An algorithm comparison
2022 · External reference
Image recognition using convolutional neural networks for classification of honey bee subspecies
10.1007/s13592-022-00918-5 · 2022 · External reference
Bees detection on images: Study of different color models for neural networks
2018 · External reference
Unresolved reference
External reference
Unresolved reference
External reference
Economic valuation of the vulnerability of world agriculture confronted with pollinator decline
10.1016/j.ecolecon.2008.06.014 · 2009 · External reference
Main causes of producing honey bee colony losses in southwestern spain: a novel machine learning-based approach
10.1007/s13592-024-01108-1 · 2024 · External reference
Antennal movements can be used as behavioral readout of odor valence in honey bees
10.1016/j.ibneur.2022.04.005 · 2022 · External reference
Automated monitoring of honey bees with barcodes and artificial intelligence reveals two distinct social networks from a single affiliative behavior
10.1038/s41598-022-26825-4 · 2023 · External reference
A comparative study of hybrid machine-learning vs. deep-learning approaches for varroa mite detection and counting
10.3390/s25165075 · 2025 · External reference
Automated assay and differential model of western honey bee (Apis mellifera) autogrooming using digital image processing
10.1016/j.compag.2017.02.003 · 2017 · External reference
MOMENT: A family of open time-series foundation models
2024 · External reference
Honey bee colony loss rates in 37 countries using the coloss survey for winter 2019–2020: the combined effects of operation size, migration and queen replacement
10.1080/00218839.2022.2113329 · 2022 · External reference
Video-based deep learning deciphers honeybee waggle dances in natural conditions
10.1007/s10980-025-02244-4 · 2025 · External reference
Toward an intelligent and efficient beehive: A survey of precision beekeeping systems and services
10.1016/j.compag.2021.106604 · 2022 · External reference
Motion-based domain randomization for detecting honey bees inside a hive
10.2352/ei.2024.36.8.image-240 · 2024 · External reference
Evaluating audio feature extraction methods for identifying bee queen presence
2023 · External reference
Signal processing the acoustics of honeybees (Apis mellifera) to identify the ‘queenless’ state in hives
2013 · External reference
Unresolved reference
2016 · External reference
Empirical analysis of honeybees acoustics as biosensors signals for swarm prediction in beehives
10.1109/access.2024.3471895 · 2024 · External reference
IoT and AI systems for enhancing bee colony strength in precision beekeeping: A survey and future research directions
10.1109/jiot.2024.3461775 · 2024 · External reference
Individual differences in honey bee behavior enabled by plasticity in brain gene regulatory networks
10.7554/elife.62850 · 2020 · External reference
Deep learning-based classification models for beehive monitoring
10.1016/j.ecoinf.2021.101353 · 2021 · External reference
A deep learning approach to classify the honeybee species and health identification
2021 · External reference
Stereoscopic motion analysis in densely packed clusters: 3D analysis of the shimmering behaviour in giant honey bees
10.1186/1742-9994-8-3 · 2011 · External reference
A CNN-based identification of honeybees’ infection using augmentation
2022 · External reference
Automated classification of bees and hornet using acoustic analysis of their flight sounds
10.1007/s13592-018-0619-6 · 2019 · External reference
Honey sources: neural network approach to bee species classification
10.1016/j.procs.2021.08.067 · 2021 · External reference
Deep learning-based detection of honey storage areas in Apis mellifera colonies for predicting physical parameters of honey via linear regression
10.3390/insects16060575 · 2025 · External reference
A color moments-based method for detection of honey bee diseases
2024 · External reference
Acoustic scene classification and visualization of beehive sounds using machine learning algorithms and Grad-CAM
2021 · External reference
A new approach for the simultaneous tracking of multiple honeybees for analysis of hive behavior
10.1007/s13592-011-0060-6 · 2011 · External reference
Segment anything
2023 · External reference
Importance of pollinators in changing landscapes for world crops
10.1098/rspb.2006.3721 · 2006 · External reference
Individual honey bee tracking in a beehive environment using deep learning and Kalman filter
10.1038/s41598-023-44718-y · 2024 · External reference
Spectral components of honey bee sound signals recorded inside and outside the beehive: An explainable machine learning approach to diurnal pattern recognition
10.3390/s25144424 · 2025 · External reference
Discrete time series forecasting of hive weight, in-hive temperature, and hive entrance traffic in non-invasive monitoring of managed honey bee colonies: Part i
10.3390/s24196433 · 2024 · External reference
On video analysis of omnidirectional bee traffic: Counting bee motions with motion detection and image classification
10.3390/app9183743 · 2019 · External reference
A novel convolutional neural network architecture for pollen-bearing honeybee recognition
2023 · External reference
Effectiveness of transfer learning, convolutional neural network and standard machine learning in computer vision assisted bee health assessment
2022 · External reference
Developing a multimodal system for bee object detection and health assessment
10.1109/access.2024.3464559 · 2024 · External reference
MFCC selection by LASSO for honey bee classification
10.3390/app14020913 · 2024 · External reference
Non-intrusive system for honeybee recognition based on audio signals and maximum likelihood classification by autoencoder
10.3390/s24165389 · 2024 · External reference
Accurate identification of native asian honey bee populations in Jilong (Xizang, China) by population genomics and deep learning
10.3390/insects16080788 · 2025 · External reference
Beemind AI: Development of an artificial intelligence-based system to assess honeybee health, behavior, and nutrient effects
2024 · External reference
Honeybee colony growth period recognition based on multivariate temperature feature extraction and machine learning
2025 · External reference
Bee hive traffic monitoring by tracking bee flight paths
2018 · External reference
Unresolved reference
2022 · External reference
Deepbees - building and scaling convolutional neuronal nets for fast and large-scale visual monitoring of bee hives
2019 · External reference
Unresolved reference
2023 · External reference
Application of digital particle image velocimetry to insect motion: Measurement of incoming, outgoing, and lateral honeybee traffic
10.3390/app10062042 · 2020 · External reference
Intellibeehive: An automated honey bee, pollen, and Varroa Destructor monitoring system
2024 · External reference
Automated monitoring and analyses of honey bee pollen foraging behavior using a deep learning-based imaging system
10.1016/j.compag.2021.106239 · 2021 · External reference
Honey bees find the shortest path: A collective flow-mediated approach
10.1007/s10015-022-00816-0 · 2022 · External reference
Improving pollen-bearing honey bee detection from videos captured at hive entrance by combining deep learning and handling imbalance techniques
10.1016/j.ecoinf.2024.102744 · 2024 · External reference
Genetic programming for bee audio classification
2023 · External reference
Varroa destructor: how does it harm Apis mellifera honey bees and what can be done about it?
10.1042/etls20190125 · 2020 · External reference
Unresolved reference
2021 · External reference
Audio-based identification of beehive states
2019 · External reference
Varroa Destructor classification using legendre–fourier moments with different color spaces
10.3390/jimaging9070144 · 2023 · External reference
Bioinspired small language models in edge systems for bee colony monitoring and control
2025 · External reference
Using honey bee flight activity data and a deep learning model as a toxicovigilance tool
10.1016/j.ecoinf.2024.102653 · 2024 · External reference
The PRISMA 2020 statement: an updated guideline for reporting systematic reviews
10.1136/bmj.n71 · 2021 · External reference
Identification of honeybees with paint codes using convolutional neural networks
2024 · External reference
Parameters influencing queen body mass and their importance as determined by machine learning in honey bees (Apis mellifera carnica)
10.1007/s13592-019-00683-y · 2019 · External reference
Remote beehive monitoring using acoustic signals
2014 · External reference
Identify the beehive sound using deep learning
2022 · External reference
Detection of the mite Varroa destructor in honey bee cells by video sequence processing
2012 · External reference
The prediction of swarming in honeybee colonies using vibrational spectra
10.1038/s41598-020-66115-5 · 2020 · External reference
Semi-automatic analysis of cells in honeybee comb images
2023 · External reference
Unresolved reference
2020 · External reference
Towards computer vision and deep learning facilitated pollination monitoring for agriculture
2021 · External reference
Buzzing through data: Advancing bee species identification with machine learning
10.3390/asi7040062 · 2024 · External reference
Understanding the enemy: A review of the genetics, behavior and chemical ecology of Varroa destructor, the parasitic mite of Apis mellifera
10.1093/jisesa/ieab101 · 2022 · External reference
Convolutional neural networks for real time classification of beehive acoustic patterns on constrained devices
10.3390/s24196384 · 2024 · External reference
Addressing multidimensional highly correlated data for forecasting in precision beekeeping
10.1016/j.compag.2024.109390 · 2024 · External reference
Predicting internal conditions of beehives using precision beekeeping
10.1016/j.biosystemseng.2022.06.006 · 2022 · External reference
Deepwings©: Automatic wing geometric morphometrics classification of honey bee (Apis mellifera) subspecies using deep learning for detecting landmarks
10.3390/bdcc6030070 · 2022 · External reference
Automated video monitoring of unmarked and marked honey bees at the hive entrance
10.3389/fcomp.2021.769338 · 2022 · External reference
Unresolved reference
2018 · External reference
Machine learning-based bee recognition and tracking for advancing insect behavior research
10.1007/s10462-024-10879-z · 2024 · External reference
Bee detection in bee hives using selective features from acoustic data
10.1007/s11042-023-15192-5 · 2023 · External reference
Identifying queenlessness in honeybee hives from audio signals using machine learning
10.3390/electronics12071627 · 2023 · External reference
Unresolved reference
2017 · External reference
Bee hive acoustic monitoring and processing using convolutional neural network and machine learning
2024 · External reference
Image-based classification of honeybees
2020 · External reference
10.1007/978-3-319-93000-8_52
10.1007/978-3-319-93000-8_52 · External reference
Anomaly detection at the apiary: Predicting state and swarming preparation activity of honey bee colonies using low-cost sensor technology
2022 · External reference
Unsupervised anomaly detection on multisensory data from honey bee colonies
2020 · External reference
Soundscape indices: New features for classifying beehive audio samples
10.13102/sociobiology.v67i4.5860 · 2020 · External reference
Bee disease Varroa prediction: Utilizing convolutional neural networks with augmentation for robust detection and identification of honeybee infection
2024 · External reference
Automated tracking and analysis of behavior in restrained insects
10.1016/j.jneumeth.2014.10.021 · 2015 · External reference
RenderGAN: Generating realistic labeled data
10.3389/frobt.2018.00066 · 2018 · External reference
Unresolved reference
2018 · External reference
Evaluation of single-shot object detection models for identifying fanning behavior in honeybees at the hive entrance
10.3390/agriculture15151609 · 2025 · External reference
Toward bee motion pattern identification on hive landing board
2023 · External reference
Toward bee behavioral pattern recognition on hive entrance using YOLOv8
2023 · External reference
Visual recognition of honeybee behavior patterns at the hive entrance
10.1371/journal.pone.0318401 · 2025 · External reference
MFCC-based descriptor for bee queen presence detection
10.1016/j.eswa.2022.117104 · 2022 · External reference
Image-based south asian bee species identification: A machine learning approach
10.1007/s10841-025-00691-7 · 2025 · External reference
Unresolved reference
2018 · External reference
Wasp detection system using AI technology to support honey bee farming
2024 · External reference
Analyses of audio and video recordings for detecting a honey bee hive robbery
2020 · External reference
Pollinators as data collectors: Estimating floral diversity with bees and computer vision
2023 · External reference
Comparison of feature extraction methods for sound-based classification of honey bee activity
10.1109/taslp.2021.3133194 · 2021 · External reference
Unresolved reference
2018 · External reference
Recognizing beehives’ health abnormalities based on mobile net deep learning model
10.1007/s44196-023-00311-9 · 2023 · External reference
A deep learning-based approach for bee sound identification
10.1016/j.ecoinf.2023.102274 · 2023 · External reference
A deep learning-based approach for bee sound identification
10.1016/j.ecoinf.2023.102274 · 2023 · External reference
Unresolved reference
External reference
Automatic behaviour analysis system for honeybees using computer vision
10.1016/j.compag.2016.01.011 · 2016 · External reference
Autonomous tracking of honey bee behaviors over long-term periods with cooperating robots
10.1126/scirobotics.adn6848 · 2024 · External reference
Deep semantic segmentation applied to honey bee comb cells
10.22456/2175-2745.143318 · 2025 · External reference
Temporal encoding strategies for YOLO-based detection of honeybee trophallaxis behavior in precision livestock systems
10.3390/agriculture15222338 · 2025 · External reference
Apis mellifera bee verification with IoT and graph neural network
10.3390/app15147969 · 2025 · External reference
Deep learning beehive monitoring system for early detection of the Varroa mite
10.3390/signals3030030 · 2022 · External reference
Automatic methods for long-term tracking and the detection and decoding of communication dances in honeybees
10.3389/fevo.2015.00103 · 2015 · External reference
Automatic detection and decoding of honey bee waggle dances
10.1371/journal.pone.0188626 · 2017 · External reference
Social networks predict the life and death of honey bees
2020 · External reference
Unresolved reference
2018 · External reference
Unresolved reference
2019 · External reference
A model for pollen measurement using video monitoring of honey bees
2017 · External reference
An AI-based open-source software for Varroa mite fall analysis in honeybee colonies
10.3390/agriculture15090969 · 2025 · External reference
An explainable AI-based hybrid machine learning model for interpretability and enhanced crop yield prediction
10.1016/j.mex.2025.103442 · 2025 · External reference
Bee swarm activity acoustic classification for an IoT-based farm service
10.3390/s20010021 · 2019 · External reference
IoT-based bee swarm activity acoustic classification using deep neural networks
10.3390/s21030676 · 2021 · External reference
Automated honey bee subspecies identification using advanced wing venation analysis and adaptive hierarchical clustering
10.1002/ece3.72101 · ExternalCitation · doi-reference
Real-time insect tracking and monitoring with computer vision and deep learning
10.1002/rse2.245 · ExternalCitation · doi-reference
10.1007/978-3-319-93000-8_52
10.1007/978-3-319-93000-8_52 · ExternalCitation · doi-reference
Honey bees find the shortest path: A collective flow-mediated approach
10.1007/s10015-022-00816-0 · ExternalCitation · doi-reference
Machine learning-based bee recognition and tracking for advancing insect behavior research
10.1007/s10462-024-10879-z · ExternalCitation · doi-reference
Image-based south asian bee species identification: A machine learning approach
10.1007/s10841-025-00691-7 · ExternalCitation · doi-reference
Video-based deep learning deciphers honeybee waggle dances in natural conditions
10.1007/s10980-025-02244-4 · ExternalCitation · doi-reference
Bee detection in bee hives using selective features from acoustic data
10.1007/s11042-023-15192-5 · ExternalCitation · doi-reference
A new approach for the simultaneous tracking of multiple honeybees for analysis of hive behavior
10.1007/s13592-011-0060-6 · ExternalCitation · doi-reference
Automated classification of bees and hornet using acoustic analysis of their flight sounds
10.1007/s13592-018-0619-6 · ExternalCitation · doi-reference
Parameters influencing queen body mass and their importance as determined by machine learning in honey bees (Apis mellifera carnica)
10.1007/s13592-019-00683-y · ExternalCitation · doi-reference
Image recognition using convolutional neural networks for classification of honey bee subspecies
10.1007/s13592-022-00918-5 · ExternalCitation · doi-reference
Main causes of producing honey bee colony losses in southwestern spain: a novel machine learning-based approach
10.1007/s13592-024-01108-1 · ExternalCitation · doi-reference
Recognizing beehives’ health abnormalities based on mobile net deep learning model
10.1007/s44196-023-00311-9 · ExternalCitation · doi-reference
Predicting internal conditions of beehives using precision beekeeping
10.1016/j.biosystemseng.2022.06.006 · ExternalCitation · doi-reference
An imaging system for monitoring the in-and-out activity of honey bees
10.1016/j.compag.2012.08.006 · ExternalCitation · doi-reference
Automatic behaviour analysis system for honeybees using computer vision
10.1016/j.compag.2016.01.011 · ExternalCitation · doi-reference
Automated assay and differential model of western honey bee (Apis mellifera) autogrooming using digital image processing
10.1016/j.compag.2017.02.003 · ExternalCitation · doi-reference
A computer vision system to monitor the infestation level of Varroa destructor in a honeybee colony
10.1016/j.compag.2019.104898 · ExternalCitation · doi-reference
Automatic detection and classification of honey bee comb cells using deep learning
10.1016/j.compag.2020.105244 · ExternalCitation · doi-reference
Automated monitoring and analyses of honey bee pollen foraging behavior using a deep learning-based imaging system
10.1016/j.compag.2021.106239 · ExternalCitation · doi-reference
Toward an intelligent and efficient beehive: A survey of precision beekeeping systems and services
10.1016/j.compag.2021.106604 · ExternalCitation · doi-reference
Detection of anomalies in bee colony using transitioning state and contrastive autoencoders
10.1016/j.compag.2022.107207 · ExternalCitation · doi-reference
Machine learning and computer vision techniques in continuous beehive monitoring applications: A survey
10.1016/j.compag.2023.108560 · ExternalCitation · doi-reference
Addressing multidimensional highly correlated data for forecasting in precision beekeeping
10.1016/j.compag.2024.109390 · ExternalCitation · doi-reference
Image-based species identification of wild bees using convolutional neural networks
10.1016/j.ecoinf.2019.101017 · ExternalCitation · doi-reference
Deep learning-based classification models for beehive monitoring
10.1016/j.ecoinf.2021.101353 · ExternalCitation · doi-reference
A deep learning-based approach for bee sound identification
10.1016/j.ecoinf.2023.102274 · ExternalCitation · doi-reference
Using honey bee flight activity data and a deep learning model as a toxicovigilance tool
10.1016/j.ecoinf.2024.102653 · ExternalCitation · doi-reference
Improving pollen-bearing honey bee detection from videos captured at hive entrance by combining deep learning and handling imbalance techniques
10.1016/j.ecoinf.2024.102744 · ExternalCitation · doi-reference
Economic valuation of the vulnerability of world agriculture confronted with pollinator decline
10.1016/j.ecolecon.2008.06.014 · ExternalCitation · doi-reference
MFCC-based descriptor for bee queen presence detection
10.1016/j.eswa.2022.117104 · ExternalCitation · doi-reference
A machine learning-based multiclass classification model for bee colony anomaly identification using an IoT-based audio monitoring system with an edge computing framework
10.1016/j.eswa.2024.124898 · ExternalCitation · doi-reference
Antennal movements can be used as behavioral readout of odor valence in honey bees
10.1016/j.ibneur.2022.04.005 · ExternalCitation · doi-reference
Artificial intelligence-driven tool for spectral analysis: identifying pesticide contamination in bees from reflectance profiling
10.1016/j.jhazmat.2024.136425 · ExternalCitation · doi-reference
Automated tracking and analysis of behavior in restrained insects
10.1016/j.jneumeth.2014.10.021 · ExternalCitation · doi-reference
An explainable AI-based hybrid machine learning model for interpretability and enhanced crop yield prediction
10.1016/j.mex.2025.103442 · ExternalCitation · doi-reference
Honey sources: neural network approach to bee species classification
10.1016/j.procs.2021.08.067 · ExternalCitation · doi-reference
Markerless tracking of an entire honey bee colony
10.1038/s41467-021-21769-1 · ExternalCitation · doi-reference
Automated computer-based detection of encounter behaviours in groups of honeybees
10.1038/s41598-017-17863-4 · ExternalCitation · doi-reference
The prediction of swarming in honeybee colonies using vibrational spectra
10.1038/s41598-020-66115-5 · ExternalCitation · doi-reference
Automated monitoring of honey bees with barcodes and artificial intelligence reveals two distinct social networks from a single affiliative behavior
10.1038/s41598-022-26825-4 · ExternalCitation · doi-reference
Individual honey bee tracking in a beehive environment using deep learning and Kalman filter
10.1038/s41598-023-44718-y · ExternalCitation · doi-reference
Varroa destructor: how does it harm Apis mellifera honey bees and what can be done about it?
10.1042/etls20190125 · ExternalCitation · doi-reference
Honey bee colony loss rates in 37 countries using the coloss survey for winter 2019–2020: the combined effects of operation size, migration and queen replacement
10.1080/00218839.2022.2113329 · ExternalCitation · doi-reference
A national survey of managed honey bee colony losses in the usa: Results from the bee informed partnership for 2020–21 and 2021–22
10.1080/00218839.2023.2264601 · ExternalCitation · doi-reference
Understanding the enemy: A review of the genetics, behavior and chemical ecology of Varroa destructor, the parasitic mite of Apis mellifera
10.1093/jisesa/ieab101 · ExternalCitation · doi-reference
Importance of pollinators in changing landscapes for world crops
10.1098/rspb.2006.3721 · ExternalCitation · doi-reference
An intelligent monitoring system for assessing bee hive health
10.1109/access.2021.3089538 · ExternalCitation · doi-reference
Developing a multimodal system for bee object detection and health assessment
10.1109/access.2024.3464559 · ExternalCitation · doi-reference
Empirical analysis of honeybees acoustics as biosensors signals for swarm prediction in beehives
10.1109/access.2024.3471895 · ExternalCitation · doi-reference
IoT and AI systems for enhancing bee colony strength in precision beekeeping: A survey and future research directions
10.1109/jiot.2024.3461775 · ExternalCitation · doi-reference
Honey bee piping detection utilizing convolutional neural networks
10.1109/jsen.2025.3531698 · ExternalCitation · doi-reference
A machine learning approach for queen bee detection through remote audio sensing to safeguard honeybee colonies
10.1109/tafe.2024.3406648 · ExternalCitation · doi-reference
Comparison of feature extraction methods for sound-based classification of honey bee activity
10.1109/taslp.2021.3133194 · ExternalCitation · doi-reference
Automated identification of honey bee pollen loads for field-applied palynological studies
10.1111/nph.70435 · ExternalCitation · doi-reference
Autonomous tracking of honey bee behaviors over long-term periods with cooperating robots
10.1126/scirobotics.adn6848 · ExternalCitation · doi-reference
The PRISMA 2020 statement: an updated guideline for reporting systematic reviews
10.1136/bmj.n71 · ExternalCitation · doi-reference
Detecting and tracking honeybees in 3D at the beehive entrance using stereo vision
10.1186/1687-5281-2013-59 · ExternalCitation · doi-reference
Stereoscopic motion analysis in densely packed clusters: 3D analysis of the shimmering behaviour in giant honey bees
10.1186/1742-9994-8-3 · ExternalCitation · doi-reference
Soundscape indices: New features for classifying beehive audio samples
10.13102/sociobiology.v67i4.5860 · ExternalCitation · doi-reference
Automatic detection and decoding of honey bee waggle dances
10.1371/journal.pone.0188626 · ExternalCitation · doi-reference
Visual recognition of honeybee behavior patterns at the hive entrance
10.1371/journal.pone.0318401 · ExternalCitation · doi-reference
Deep semantic segmentation applied to honey bee comb cells
10.22456/2175-2745.143318 · ExternalCitation · doi-reference
Motion-based domain randomization for detecting honey bees inside a hive
10.2352/ei.2024.36.8.image-240 · ExternalCitation · doi-reference
Automated video monitoring of unmarked and marked honey bees at the hive entrance
10.3389/fcomp.2021.769338 · ExternalCitation · doi-reference
Automatic methods for long-term tracking and the detection and decoding of communication dances in honeybees
10.3389/fevo.2015.00103 · ExternalCitation · doi-reference
Tracking all members of a honey bee colony over their lifetime using learned models of correspondence
10.3389/frobt.2018.00035 · ExternalCitation · doi-reference
RenderGAN: Generating realistic labeled data
10.3389/frobt.2018.00066 · ExternalCitation · doi-reference
An AI-based open-source software for Varroa mite fall analysis in honeybee colonies
10.3390/agriculture15090969 · ExternalCitation · doi-reference
Evaluation of single-shot object detection models for identifying fanning behavior in honeybees at the hive entrance
10.3390/agriculture15151609 · ExternalCitation · doi-reference
Temporal encoding strategies for YOLO-based detection of honeybee trophallaxis behavior in precision livestock systems
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