Use of Annotated Image Data for Fruit Diversity Analysis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F24%3A43925846" target="_blank" >RIV/62156489:43110/24:43925846 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.11118/978-80-7509-990-7-0084" target="_blank" >https://doi.org/10.11118/978-80-7509-990-7-0084</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.11118/978-80-7509-990-7-0084" target="_blank" >10.11118/978-80-7509-990-7-0084</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Use of Annotated Image Data for Fruit Diversity Analysis

Popis výsledku v původním jazyce

This paper deals with a method of development of an annotated image dataset for the detection and classification of plant tissues, aimed at supporting automation in agriculture. The work includes a collection of high-definition image data, their annotation and utility scripts, with the aim of creating a universally accessible dataset for the scientific community. The method is designed to be compatible with off-the-shelf hardware, in order to better support research and development in the field of automated plant identification and plant disease diagnostics. This approach has the potential to significantly improve the efficiency of cultivation processes and support the implementation of advanced technologies in the agricultural sector, along with the automation of this sector.

Název v anglickém jazyce

Use of Annotated Image Data for Fruit Diversity Analysis

Popis výsledku anglicky

This paper deals with a method of development of an annotated image dataset for the detection and classification of plant tissues, aimed at supporting automation in agriculture. The work includes a collection of high-definition image data, their annotation and utility scripts, with the aim of creating a universally accessible dataset for the scientific community. The method is designed to be compatible with off-the-shelf hardware, in order to better support research and development in the field of automated plant identification and plant disease diagnostics. This approach has the potential to significantly improve the efficiency of cultivation processes and support the implementation of advanced technologies in the agricultural sector, along with the automation of this sector.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/EF16_017%2F0002334" target="_blank" >EF16_017/0002334: Výzkumná infrastruktura pro mladé vědce</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

26th International Conference Economic Competitiveness and Sustainability: Proceedings

ISBN

978-80-7509-990-7

ISSN

—

e-ISSN

—

Počet stran výsledku

9

Strana od-do

84-92

Název nakladatele

Mendelova univerzita v Brně

Místo vydání

Brno

Místo konání akce

Brno

Datum konání akce

21. 3. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—