Classification of timber load on trucks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27230%2F20%3A10245761" target="_blank" >RIV/61989100:27230/20:10245761 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.astesj.com/publications/ASTESJ_050284.pdf" target="_blank" >http://www.astesj.com/publications/ASTESJ_050284.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.25046/aj050284" target="_blank" >10.25046/aj050284</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Classification of timber load on trucks

Popis výsledku v původním jazyce

All trucks heading into the paper mill MONDI, Slovakia, have to pass an automatic security check. It controls if storage of its wood load meets all standards of safety. Each truck is scanned by a group of 2D scanners. After that the inspection of timber load is done by a software with use of the data gained by these scanners. The security software is universal for all kinds of storage of timber loads. This article is dedicated to deal with a problem of classification a kind of wood storage on a semi-trailer. The classification is solved by training a convolutional neural network on datasets with recorded trucks of both kinds to learn patterns distinguishing them. The image classification is done with use of images recorded by a set of cameras. By determining a type of storage, it is possible to execute the safety check for a specific type of wood load with better result than the universal check. (C) 2020 ASTES Publishers. All rights reserved.

Název v anglickém jazyce

Classification of timber load on trucks

Popis výsledku anglicky

All trucks heading into the paper mill MONDI, Slovakia, have to pass an automatic security check. It controls if storage of its wood load meets all standards of safety. Each truck is scanned by a group of 2D scanners. After that the inspection of timber load is done by a software with use of the data gained by these scanners. The security software is universal for all kinds of storage of timber loads. This article is dedicated to deal with a problem of classification a kind of wood storage on a semi-trailer. The classification is solved by training a convolutional neural network on datasets with recorded trucks of both kinds to learn patterns distinguishing them. The image classification is done with use of images recorded by a set of cameras. By determining a type of storage, it is possible to execute the safety check for a specific type of wood load with better result than the universal check. (C) 2020 ASTES Publishers. All rights reserved.

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

—

OECD FORD obor

20301 - Mechanical engineering

Projekt

<a href="/cs/project/EF16_019%2F0000867" target="_blank" >EF16_019/0000867: Centrum výzkumu pokročilých mechatronických systémů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název periodika

Advances in Science, Technology and Engineering Systems

ISSN

2415-6698

e-ISSN

—

Svazek periodika

5

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

5

Strana od-do

683-687

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85084860033