| dc.contributor.author | Sledevič, Tomyslav | |
| dc.contributor.author | Abromavičius, Vytautas | |
| dc.date.accessioned | 2023-09-18T16:41:13Z | |
| dc.date.available | 2023-09-18T16:41:13Z | |
| dc.date.issued | 2023 | |
| dc.identifier.issn | 2831-5634 | |
| dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/115988 | |
| dc.description.abstract | The ability to predict bee behavior through visual analysis of their activity at the hive entrance provides valuable insight into the hive's condition. In this study, we present an algorithm for visual monitoring of bee behavior implemented based on open source tools. The convolutional neural network (CNN) is used to detect bees on the landing board of the hive. The YOLOv8m CNN detects bees with 0.97% mAP@0.5 and 0.65% mAP@0.5:0.95 mean average precision, respectively. Bee behavior types such as foraging, fanning, and washboarding are presented in heat and path maps. The speed patterns are used to identify the type of motion of the bees. | eng |
| dc.format | PDF | |
| dc.format.extent | p. 1-4 | |
| dc.format.medium | tekstas / txt | |
| dc.language.iso | eng | |
| dc.relation.isreferencedby | IEEE Xplore | |
| dc.relation.isreferencedby | Scopus | |
| dc.title | Toward bee motion pattern identification on hive landing board | |
| dc.type | Straipsnis konferencijos darbų leidinyje Scopus DB / Paper in conference publication in Scopus DB | |
| dcterms.accessRights | PART NUMBER: CFP2347Z-ART | |
| dcterms.references | 8 | |
| dc.type.pubtype | P1b - Straipsnis konferencijos darbų leidinyje Scopus DB / Article in conference proceedings Scopus DB | |
| dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
| dc.contributor.faculty | Elektronikos fakultetas / Faculty of Electronics | |
| dc.subject.researchfield | T 001 - Elektros ir elektronikos inžinerija / Electrical and electronic engineering | |
| dc.subject.studydirection | E09 - Elektronikos inžinerija / Electronic engineering | |
| dc.subject.vgtuprioritizedfields | IK0202 - Išmaniosios signalų apdorojimo ir ryšių technologijos / Smart Signal Processing and Telecommunication Technologies | |
| dc.subject.ltspecializations | L106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies | |
| dc.subject.en | convolutional neural network | |
| dc.subject.en | bee detection | |
| dc.subject.en | object tracking | |
| dcterms.sourcetitle | 2023 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream), 27 April 2023, Vilnius, Lithuania / organized by Vilnius Gediminas Technical University | |
| dc.publisher.name | IEEE | |
| dc.publisher.city | Piscataway, NJ | |
| dc.identifier.doi | 10.1109/eStream59056.2023.10134852 | |
| dc.identifier.elaba | 168061021 | |
