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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Firat, O. Tursun, O.T. Vural, F.T.Y. |
| Copyright Year | 2012 |
| Description | Author affiliation: Bilgisayar Mühendisliği Bölümü, Orta Doğu Teknik Üniversitesi, Ankara, Turkey (Firat, O.; Tursun, O.T.; Vural, F.T.Y.) |
| Abstract | In literature, many target-specific methods are available for target detection on satellite images. Yet for many targets, intra-class variance is high. This situation results in decreased detection performance after generalization. Airfield is one of the targets with high intra-class variance in satellite images. This variance is caused by different compositions observed in airfields. Hence, approaches which aim at detecting airfields in specific regions and compositions are either unsuccessful or inapplicable to images taken from different regions. Context invariants make it possible to generalize target detection algorithms for varying target compositions and regions. In this study, context invariants are proposed for airfield region-of-interest detection and it is observed that context invariance plays an important role in developing robust and reliable algorithm for varying region, climate and compositions. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 1224168 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467300551 |
| e-ISBN | 9781467300568 |
| e-ISBN | 9781467300544 |
| DOI | 10.1109/SIU.2012.6204767 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-04-18 |
| Publisher Place | Turkey |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Context Satellites Terrain mapping Object detection Airports Indexes Level measurement |
| Content Type | Text |
| Resource Type | Article |
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