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Dergiler / Sakarya University Journal of Science / 2026 / Volume: 24 Issue: 1

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

Ferhat Ucar(FIRAT UNIVERSITY)0000-0001-9366-6124
Deniz Korkmaz(Malatya Turgut Ozal University, Department of Electrical Engineering, Malatya, Turkey)0000-0002-5159-0659
Sayfa
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Yayın Tarihi
2020-02-01
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Yapay Zeka Hızlı Bakış & Çıkarımlar

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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Visual and graphical results of features at various layers and deconvolutions are also demonstrated for a better understanding of the basic process.

📌 3 Maddede Bu Makale

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Amaç & Hipotez: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.
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Temel Bulgular & Veri: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.
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Sonuç & Katkı:Visual and graphical results of features at various layers and deconvolutions are also demonstrated for a better understanding of the basic process.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:deep convolutional neural networks (CNNs) · ship target classification · remote sensing

Abstract

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.

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Bu Makaleye Atıf Yap

Ucar, F., Korkmaz, D. (2020). A Ship Detector Design Based on Deep Convolutional Neural Networks for Satellite Images. Sakarya University Journal of Science, Volume: 24 Issue: 1. https://doi.org/10.16984/saufenbilder.587731

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Kaynakça (17)

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