Naslov
Comparison of Cogent Confabulation Based Classifier and Naive Bayes Classifier in the Detection of Lens Flares in Wildfire Smoke Detection

Autori
Braović, Maja ; Stipaničev, Darko ; Gotovac, Dunja ; Krstinić, Damir

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of 2ND INTERNATIONAL MULTIDISCIPLINARY CONFERENCE ON COMPUTER AND ENERGY SCIENCE (SPLITTECH 2017) / - Split : Fakultet elektrotehnike, strojarstva i brodogradnje Sveučilišta u Splitu, 2017, 1-4

ISBN
978-953-290-071-2

Skup
2nd International Multidisciplinary Conference on Computer and Energy Science (SpliTech 2017)

Mjesto i datum
Split, Hrvatska, 12.07.2017. - 14.07.2017

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Rad nema ključnih riječi
(The paper has no keywords)

Sažetak
In automatic and image processing based wildfire smoke detection various spatial and temporal procedures are used to detect certain wildfire features. The final step is usually the classification procedure that finally decides if some detected phenomena represents wildfire smoke or not. In classification procedure various classifiers can be used, but as the system has to work in real time and usually on limited hardware, the efforts of researchers working on those systems are usually aimed towards the implementation of classifiers that are simple for implementation and fast in execution. In this paper the emphasis is on the comparison of two simple and fast classifiers - the cogent confabulation based classifier and the Naive Bayes classifier. Even though they can appear similar, on the theoretical and philosophical level they are quite different. Besides the theoretical comparison of both classifiers they are also compared on an example of lens flare detection in images taken from wildfire smoke surveillance cameras video streams.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA