Learning from Depth Sensor Data using Inductive Logic Programming (CROSBI ID 629080)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Drole, Miha ; Vračar, Petar ; Stančić, Ivo ; Musić, Josip ; Panjkota, Ante ; Kononenko, Igor ; Kukar, Matjaž
engleski
Learning from Depth Sensor Data using Inductive Logic Programming
The problem of detecting objects and their movements in sensor data is of crucial importance in providing safe navigation through both indoor and outdoor environments for the visually impaired. In our setting we use depth- sensor data obtained from a simulator and use inductive logic programming (ILP), a subfield of machine learning that deals with learning concept descriptions, to learn how to detect borders, find the border that is nearest to some point of interest, and border correspondence through time. We demonstrate how ILP can be used to tackle this problem in an incremental manner by using previously learned predicates to construct more complex ones. The learned concept descriptions show high (> 90%) accuracy and their natural language interpretation closely matches an intuitive understanding of their meaning.
supervised learning; context awareness; assistive devices; knowlegde discovery
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
Podaci o prilogu
2015.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the 2015 XXV International Conference on Information, Communication and Automation Technologies (ICAT)
Ribić, Samir ; Zajko, Ernedin ; Sadžak, Aida
Sarajevo: Institute of Electrical and Electronics Engineers (IEEE)
978-1-4673-8145-1
Podaci o skupu
2015 XXV International Conference on Information, Communication and Automation Technologies (ICAT)
predavanje
29.10.2015-31.10.2015
Sarajevo, Bosna i Hercegovina