POLLEN BEARING HONEY BEE DETECTION IN HIVE ENTRANCE VIDEO RECORDED BY REMOTE EMBEDDED SYSTEM FOR POLLINATION MONITORING

17 citations as recorded by crossref.

1. An Approximate GEMM Unit for Energy-Efficient Object Detection R. Pilipović et al. 10.3390/s21124195
2. Honeybee flight dynamics and pair separation in windy conditions near the hive entrance B. Hejazi et al. 10.1088/1367-2630/acf8ec
3. Application of Digital Particle Image Velocimetry to Insect Motion: Measurement of Incoming, Outgoing, and Lateral Honeybee Traffic S. Mukherjee & V. Kulyukin 10.3390/app10062042
4. Deep learning-based classification models for beehive monitoring S. Kaplan Berkaya et al. 10.1016/j.ecoinf.2021.101353
5. A Method for Detection of Small Moving Objects in UAV Videos V. Stojnić et al. 10.3390/rs13040653
6. 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 V. Kulyukin et al. 10.3390/s24196433
7. BeeNet: An End-To-End Deep Network For Bee Surveillance J. Yoo et al. 10.1016/j.procs.2023.08.180
8. BeePIV: A Method to Measure Apis Mellifera Traffic with Particle Image Velocimetry in Videos V. Kulyukin et al. 10.3390/app11052276
9. Edge-Based Detection of Varroosis in Beehives with IoT Devices with Embedded and TPU-Accelerated Machine Learning D. Mrozek et al. 10.3390/app112211078
10. On Video Analysis of Omnidirectional Bee Traffic: Counting Bee Motions with Motion Detection and Image Classification V. Kulyukin & S. Mukherjee 10.3390/app9183743
11. On Image Classification in Video Analysis of Omnidirectional Apis Mellifera Traffic: Random Reinforced Forests vs. Shallow Convolutional Networks V. Kulyukin et al. 10.3390/app11178141
12. Honeybees modify flight trajectories in turbulent wind B. Hejazi et al. 10.1088/1367-2630/ac9cc4
13. Automated monitoring and analyses of honey bee pollen foraging behavior using a deep learning-based imaging system T. Ngo et al. 10.1016/j.compag.2021.106239
14. Accuracy vs. Energy: An Assessment of Bee Object Inference in Videos from On-Hive Video Loggers with YOLOv3, YOLOv4-Tiny, and YOLOv7-Tiny V. Kulyukin & A. Kulyukin 10.3390/s23156791
15. Detection of Varroa destructor Infestation of Honeybees Based on Segmentation and Object Detection Convolutional Neural Networks M. Liu et al. 10.3390/agriengineering5040102
16. Visual recognition of honeybee behavior patterns at the hive entrance T. Sledevič et al. 10.1371/journal.pone.0318401
17. Tracking individual honeybees among wildflower clusters with computer vision-facilitated pollinator monitoring M. Ratnayake et al. 10.1371/journal.pone.0239504