Year 2020, Volume 24 , Issue 1, Pages 197 - 204 2020-02-01

A Ship Detector Design Based on Deep Convolutional Neural Networks for Satellite Images

Ferhat UCAR [1] , Deniz KORKMAZ [2]


Ship target classification from satellite images is a challenging task with its requirements of feature extracting, advanced pre-processing, a variety of parameters obtained from satellites and other type of images, and analyzing of images. The dissimilarity of results, enhanced dataset requirement, intricacy of the problem domain, general use of Synthetic Aperture Radar (SAR) images and problems on generalizability are some topics of the issues related to ship target detection. In this study, we propose a deep convolutional neural network model for detecting the ships using the satellite images as inputs.  Our model has acquired an adequate accuracy value by just using a pre-processed satellite image input. Visual and graphical results of features at various layers and deconvolutions are also demonstrated for a better understanding of the basic process.

deep convolutional neural networks (CNNs), ship target classification, remote sensing, satellite imagery
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Primary Language en
Subjects Engineering, Electrical and Electronic
Published Date February 2020
Journal Section Research Articles
Authors

Orcid: 0000-0001-9366-6124
Author: Ferhat UCAR (Primary Author)
Institution: FIRAT UNIVERSITY
Country: Turkey


Orcid: 0000-0002-5159-0659
Author: Deniz KORKMAZ (Primary Author)
Institution: Malatya Turgut Ozal University, Department of Electrical Engineering, Malatya, Turkey
Country: Turkey


Dates

Application Date : July 5, 2019
Acceptance Date : December 3, 2019
Publication Date : February 1, 2020

Bibtex @research article { saufenbilder587731, journal = {Sakarya University Journal of Science}, issn = {1301-4048}, eissn = {2147-835X}, address = {}, publisher = {Sakarya University}, year = {2020}, volume = {24}, pages = {197 - 204}, doi = {10.16984/saufenbilder.587731}, title = {A Ship Detector Design Based on Deep Convolutional Neural Networks for Satellite Images}, key = {cite}, author = {UCAR, Ferhat and KORKMAZ, Deniz} }
APA UCAR, F , KORKMAZ, D . (2020). A Ship Detector Design Based on Deep Convolutional Neural Networks for Satellite Images. Sakarya University Journal of Science , 24 (1) , 197-204 . DOI: 10.16984/saufenbilder.587731
MLA UCAR, F , KORKMAZ, D . "A Ship Detector Design Based on Deep Convolutional Neural Networks for Satellite Images". Sakarya University Journal of Science 24 (2020 ): 197-204 <http://www.saujs.sakarya.edu.tr/en/issue/49430/587731>
Chicago UCAR, F , KORKMAZ, D . "A Ship Detector Design Based on Deep Convolutional Neural Networks for Satellite Images". Sakarya University Journal of Science 24 (2020 ): 197-204
RIS TY - JOUR T1 - A Ship Detector Design Based on Deep Convolutional Neural Networks for Satellite Images AU - Ferhat UCAR , Deniz KORKMAZ Y1 - 2020 PY - 2020 N1 - doi: 10.16984/saufenbilder.587731 DO - 10.16984/saufenbilder.587731 T2 - Sakarya University Journal of Science JF - Journal JO - JOR SP - 197 EP - 204 VL - 24 IS - 1 SN - 1301-4048-2147-835X M3 - doi: 10.16984/saufenbilder.587731 UR - https://doi.org/10.16984/saufenbilder.587731 Y2 - 2019 ER -
EndNote %0 Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi A Ship Detector Design Based on Deep Convolutional Neural Networks for Satellite Images %A Ferhat UCAR , Deniz KORKMAZ %T A Ship Detector Design Based on Deep Convolutional Neural Networks for Satellite Images %D 2020 %J Sakarya University Journal of Science %P 1301-4048-2147-835X %V 24 %N 1 %R doi: 10.16984/saufenbilder.587731 %U 10.16984/saufenbilder.587731
ISNAD UCAR, Ferhat , KORKMAZ, Deniz . "A Ship Detector Design Based on Deep Convolutional Neural Networks for Satellite Images". Sakarya University Journal of Science 24 / 1 (February 2020): 197-204 . https://doi.org/10.16984/saufenbilder.587731
AMA UCAR F , KORKMAZ D . A Ship Detector Design Based on Deep Convolutional Neural Networks for Satellite Images. SAUJS. 2020; 24(1): 197-204.
Vancouver UCAR F , KORKMAZ D . A Ship Detector Design Based on Deep Convolutional Neural Networks for Satellite Images. Sakarya University Journal of Science. 2020; 24(1): 204-197.