Unsupervised and Supervised Activity Analysis of Drone Sensor Data

Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F17%3A00479378" target="_blank" >RIV/67985807:_____/17:00479378 - isvavai.cz</a>
Nalezeny alternativní kódy
RIV/00216208:11320/17:10370158
Výsledek na webu
<a href="http://dx.doi.org/10.1007/978-3-319-66963-2_1" target="_blank" >http://dx.doi.org/10.1007/978-3-319-66963-2_1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-66963-2_1" target="_blank" >10.1007/978-3-319-66963-2_1</a>

Jazyk výsledku
angličtina
Název v původním jazyce
Unsupervised and Supervised Activity Analysis of Drone Sensor Data
Popis výsledku v původním jazyce
This paper deals with methods for identification of drone activities based on its sensor data. Several unsupervised and supervised approaches are proposed and tested for the task of activity analysis. We demonstrate that sensor data, although quite correlated, are still prone to standard dimensionality reduction techniques that in fact make the problem hard for unsupervised methods. On the other hand, a supervised model based on deep neural network is capable of learning the task from human operator data reformulated as a classification problem
Název v anglickém jazyce
Unsupervised and Supervised Activity Analysis of Drone Sensor Data
Popis výsledku anglicky
This paper deals with methods for identification of drone activities based on its sensor data. Several unsupervised and supervised approaches are proposed and tested for the task of activity analysis. We demonstrate that sensor data, although quite correlated, are still prone to standard dimensionality reduction techniques that in fact make the problem hard for unsupervised methods. On the other hand, a supervised model based on deep neural network is capable of learning the task from human operator data reformulated as a classification problem

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/GA15-19877S" target="_blank" >GA15-19877S: Automatické modelování znalostí a plánů pro autonomní roboty</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění
2017
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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