Name
Title | ||
|---|---|---|
Automatic Warship Recognition System : Dataset, Feature Representation and Classification Analysis |
Abstract | ||
|---|---|---|
Classification of warships plays a critical role particularly in crises and war times. While there are several studies in the literature regarding classification of civilian ship types, warship classification task is yet far from maturity, which are significantly more similar to each other compared to civilian ships. In this study, we present a dataset and propose a system that employs automatic classification of warships based on their optical images. Histogram of Oriented Gradients (HOG) features extracted from ship images were investigated after several preprocessing steps which are then used in classification with Support Vector Machines (SVM). A dataset is composed based on images of particularly similar 9 warship classes that exist in the Turkish Navy and it has been shown that the proposed approach reaches 83:8% classification accuracy. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/SIU.2019.8806462 | Signal Processing and Communications Applications Conference |
Keywords | Field | DocType |
Warship Classification,Histogram of Oriented Gradients,Support Vector Machines,Feature Extraction | Computer vision,Navy,Recognition system,Pattern recognition,Computer science,Support vector machine,Feature extraction,Histogram of oriented gradients,Preprocessor,Artificial intelligence | Conference |
ISSN | Citations | PageRank |
2165-0608 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yavuz Alper Kara | 1 | 0 | 0.34 |
| Ömer Kürsat Uçarer | 2 | 0 | 0.34 |
| Batuhan Gündogdu | 3 | 0 | 0.68 |