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Car detection in aerial images of dense urban areas

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Title: Car detection in aerial images of dense urban areas
Authors: Stathaki, P
ElMikaty, M
Item Type: Journal Article
Abstract: With the ever-increasing demand in the analysis and understanding of aerial images in order to remotely recognise targets, this paper introduces a robust system for the detection and localisation of cars in images captured by air vehicles and satellites. The system adopts a sliding-window approach. It compromises a window-evaluation and a window-classification sub-systems. The performance of the proposed framework was evaluated on the Vaihingen dataset. Results demonstrate its superiority to the state of the art.
Issue Date: 1-Feb-2018
Date of Acceptance: 11-Jul-2017
URI: http://hdl.handle.net/10044/1/50103
DOI: 10.1109/TAES.2017.2732832
ISSN: 0018-9251
Publisher: Institute of Electrical and Electronics Engineers
Start Page: 51
End Page: 63
Journal / Book Title: IEEE Transactions on Aerospace and Electronic Systems
Volume: 54
Issue: 1
Copyright Statement: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords: Science & Technology
Technology
Engineering, Aerospace
Engineering, Electrical & Electronic
Telecommunications
Engineering
VEHICLE DETECTION
RECOGNITION
CLASSIFICATION
Aerospace & Aeronautics
0901 Aerospace Engineering
0906 Electrical and Electronic Engineering
0909 Geomatic Engineering
Publication Status: Published
Online Publication Date: 2017-07-27
Appears in Collections:Electrical and Electronic Engineering
Faculty of Engineering