Detail publikačního výsledku

Computer Vision Approaches for Automated Bee Counting Application

BILÍK, Š.; JANÁKOVÁ, I.; LIGOCKI, A.; FICEK, D.; HORÁK, K.

Originální název

Computer Vision Approaches for Automated Bee Counting Application

Anglický název

Computer Vision Approaches for Automated Bee Counting Application

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

Many application from the bee colony health state monitoring could be efficiently solved using a computer vision techniques. One of such challenges is an efficient way for counting the number of incoming and outcoming bees, which could be used to further analyse many trends, such as the bee colony health state, blooming periods, or for investigating the effects of agricultural spraying. In this paper, we compare three methods for the automated bee counting over two own datasets. The best performing method is based on the ResNet-50 convolutional neural network classifier, which achieved accuracy of 87% over the BUT1 dataset and the accuracy of 93% over the BUT2 dataset.

Anglický abstrakt

Many application from the bee colony health state monitoring could be efficiently solved using a computer vision techniques. One of such challenges is an efficient way for counting the number of incoming and outcoming bees, which could be used to further analyse many trends, such as the bee colony health state, blooming periods, or for investigating the effects of agricultural spraying. In this paper, we compare three methods for the automated bee counting over two own datasets. The best performing method is based on the ResNet-50 convolutional neural network classifier, which achieved accuracy of 87% over the BUT1 dataset and the accuracy of 93% over the BUT2 dataset.

Klíčová slova

Signal Processing; Biomedical systems; bee counting; bee traffic monitoring; computer vision; deep classification; object detection

Klíčová slova v angličtině

Signal Processing; Biomedical systems; bee counting; bee traffic monitoring; computer vision; deep classification; object detection

Autoři

BILÍK, Š.; JANÁKOVÁ, I.; LIGOCKI, A.; FICEK, D.; HORÁK, K.

Rok RIV

2025

Vydáno

21.06.2024

Nakladatel

Brno University of Technology

Místo

Brno, CZ

Kniha

18th IFAC Conference on Programmable Devices and Embedded Systems PDES 2024

ISSN

2405-8963

Periodikum

IFAC-PapersOnLine

Svazek

58

Číslo

9

Stát

Spojené království Velké Británie a Severního Irska

Strany od

43

Strany do

48

Strany počet

6

URL

https://www.sciencedirect.com/science/article/pii/S2405896324004580?via%3Dihub

BibTex

@inproceedings{BUT189322,
  author="Šimon {Bilík} and Ilona {Janáková} and Adam {Ligocki} and Dominik {Ficek} and Karel {Horák}",
  title="Computer Vision Approaches for Automated Bee Counting Application",
  booktitle="18th IFAC Conference on Programmable Devices and Embedded Systems PDES 2024",
  year="2024",
  journal="IFAC-PapersOnLine",
  volume="58",
  number="9",
  pages="43--48",
  publisher="Brno University of Technology",
  address="Brno, CZ",
  doi="10.1016/j.ifacol.2024.07.369",
  issn="2405-8971",
  url="https://www.sciencedirect.com/science/article/pii/S2405896324004580?via%3Dihub"
}