| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0563135 |
| utime |
20230316105808.8 |
| mtime |
20221031235959.9 |
| SCOPUS |
85146732817 |
| DOI |
10.1109/ICIP46576.2022.9897809 |
| title
(primary) (eng) |
Monitoring of Varroa Infestation rate in Beehives: A Simple AI Approach |
| specification |
| page_count |
5 s. |
| media_type |
E |
|
| serial |
| ARLID |
cav_un_epca*0564843 |
| ISBN |
978-1-6654-9620-9 |
| ISSN |
2381-8549 |
| title
|
IEEE International Conference on Image Processing 2022 : Proceedings |
| page_num |
3341-3345 |
| publisher |
| place |
Piscataway |
| name |
IEEE |
| year |
2022 |
|
|
| keyword |
Machine learning algorithms |
| keyword |
Costs |
| keyword |
Image processing |
| keyword |
Machine learning |
| keyword |
Frequency measurement |
| keyword |
Complexity theory |
| author
(primary) |
| ARLID |
cav_un_auth*0401593 |
| name1 |
Picek |
| name2 |
L. |
| country |
CZ |
|
| author
|
| ARLID |
cav_un_auth*0283562 |
| name1 |
Novozámský |
| name2 |
Adam |
| institution |
UTIA-B |
| full_dept (cz) |
Zpracování obrazové informace |
| full_dept |
Department of Image Processing |
| department (cz) |
ZOI |
| department |
ZOI |
| full_dept |
Department of Image Processing |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0274385 |
| name1 |
Čapková Frydrychová |
| name2 |
Radmila |
| institution |
BC-A |
| full_dept (cz) |
ENTU - Molekulární biologie a genetika |
| full_dept |
Molecular Biology and Genetics |
| full_dept |
Insect Molecular Biology and Genetics |
| fullinstit |
Biologické centrum AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101238 |
| name1 |
Zitová |
| name2 |
Barbara |
| institution |
UTIA-B |
| full_dept (cz) |
Zpracování obrazové informace |
| full_dept |
Department of Image Processing |
| department (cz) |
ZOI |
| department |
ZOI |
| full_dept |
Department of Image Processing |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0050534 |
| name1 |
Mach |
| name2 |
P. |
| country |
CZ |
|
| source |
|
| cas_special |
| project |
| project_id |
StrategieAV21/1 |
| agency |
AV ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0328930 |
|
| abstract
(eng) |
This paper addresses the monitoring of Varroa destructor infestation in Western honey bee colonies. We propose a simple approach using automatic image-based analysis of the fallout on beehive bottom boards. In contrast to the existing high-tech methods, our solution does not require extensive and expensive hardware components, just a standard smart-phone. The described method has the potential to replace the time-consuming, inaccurate, and most common practice where the infestation level is evaluated manually. The underlining machine learning method combines a thresholding algorithm with a shallow CNN—VarroaNet. It provides a reliable estimate of the infestation level with a mean infestation level accuracy of 96.0% and 93.8% in the autumn and winter, respectively. Furthermore, we introduce the developed end-to-end system and its deployment into the online beekeeper’s diary—ProBee—that allows users to identify and track infestation levels on bee colonies. |
| action |
| ARLID |
cav_un_auth*0438859 |
| name |
IEEE International Conference on Image Processing 2022 /29./ |
| dates |
20221016 |
| mrcbC20-s |
20221019 |
| place |
Bordeaux |
| country |
FR |
|
| RIV |
JC |
| FORD0 |
20000 |
| FORD1 |
20200 |
| FORD2 |
20206 |
| reportyear |
2023 |
| num_of_auth |
5 |
| mrcbC47 |
BC-A 10000 10600 10613 |
| presentation_type |
PO |
| inst_support |
RVO:67985556 |
| inst_support |
RVO:60077344 |
| permalink |
https://hdl.handle.net/11104/0336399 |
| cooperation |
| ARLID |
cav_un_auth*0309068 |
| name |
Západočeská univerzita v Plzni, Fakulta aplikovaných věd |
| country |
CZ |
|
| cooperation |
| ARLID |
cav_un_auth*0304556 |
| name |
Biologické centrum AV ČR |
| institution |
BC |
| country |
CZ |
|
| confidential |
S |
| arlyear |
2022 |
| mrcbU14 |
85146732817 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
WOS |
| mrcbU63 |
cav_un_epca*0564843 IEEE International Conference on Image Processing 2022 : Proceedings IEEE 2022 Piscataway 3341 3345 978-1-6654-9620-9 2381-8549 |
|