| dc.contributor.author | Sledevič, Tomyslav | |
| dc.date.accessioned | 2023-09-18T17:05:57Z | |
| dc.date.available | 2023-09-18T17:05:57Z | |
| dc.date.issued | 2018 | |
| dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/119515 | |
| dc.description.abstract | The article presents the classification of images with pollen bearing bees using convolutional neural network (CNN). The aim is to find out a sufficient configuration of CNN required for future implementation on low-cost FPGA. A new dataset with bee images was collected on the entrances to several beehives. hidden layers with up to 15 15 x 15 down to 3x3 filter sizes. The CNN configured to three hidden layers 7–7, 5–5, 3–3 was selected for future application as a trade off between accuracy 94% and number of required arithmetic operations. | eng |
| dc.format | PDF | |
| dc.format.extent | p. 1-4 | |
| dc.format.medium | tekstas / txt | |
| dc.language.iso | eng | |
| dc.relation.isreferencedby | Conference Proceedings Citation Index - Science (Web of Science) | |
| dc.relation.isreferencedby | IEEE Xplore | |
| dc.relation.isreferencedby | Scopus | |
| dc.source.uri | https://ieeexplore.ieee.org/document/8592464 | |
| dc.title | The application of convolutional neural network for pollen bearing bee classification | |
| dc.type | Straipsnis konferencijos darbų leidinyje Web of Science DB / Paper in conference publication in Web of Science DB | |
| dcterms.references | 16 | |
| dc.type.pubtype | P1a - Straipsnis konferencijos darbų leidinyje Web of Science DB / Article in conference proceedings Web of Science 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.researchfield | T 007 - Informatikos inžinerija / Informatics engineering | |
| dc.subject.researchfield | N 001 - Matematika / Mathematics | |
| 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 | gradient descent training | |
| dc.subject.en | feature extraction | |
| dc.subject.en | pollen bearing bee | |
| dcterms.sourcetitle | 2018 IEEE. 6th workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE), November 8-10, 2018 Vilnius, Lithuania : proceedings / edited by: Dalius Navakauskas, Andrejs Romanovs, Darius Plonis | |
| dc.publisher.name | IEEE | |
| dc.publisher.city | New York | |
| dc.identifier.doi | 2-s2.0-85061510135 | |
| dc.identifier.doi | 000458738600027 | |
| dc.identifier.doi | 10.1109/AIEEE.2018.8592464 | |
| dc.identifier.elaba | 33370786 | |