- Tytuł:
- Automated approach to classification of mine-like objects using multiple-aspect sonar images
- Autorzy:
-
Wang, X.
Liu, X.
Japkowicz, N.
Matwin, S. - Powiązania:
- https://bibliotekanauki.pl/articles/91790.pdf
- Data publikacji:
- 2014
- Wydawca:
- Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
- Tematy:
-
object
sea bed
multiple side-scan sonar
Dempster-Shafer theory
DS concept
classifier
imbalance
imbalanced problem
multi-instance class - Opis:
- In this paper, the detection of mines or other objects on the seabed from multiple side-scan sonar views is considered. Two frameworks are provided for this kind of classification. The first framework is based upon the Dempster–Shafer (DS) concept of fusion from a single-view kernel-based classifier and the second framework is based upon the concepts of multi-instance classifiers. Moreover, we consider the class imbalance problem which is always presents in sonar image recognition. Our experimental results show that both of the presented frameworks can be used in mine-like object classification and the presented methods for multi-instance class imbalanced problem are also effective in such classification.
- Źródło:
-
Journal of Artificial Intelligence and Soft Computing Research; 2014, 4, 2; 133-148
2083-2567
2449-6499 - Pojawia się w:
- Journal of Artificial Intelligence and Soft Computing Research
- Dostawca treści:
- Biblioteka Nauki
Artykuł