Skripsi

IMPLEMENTASI METODE FASTER REGION CONVOLUTIONAL NEURAL NETWORK UNTUK DETEKSI KAPAL LAUT.

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Accurate and efficient ship detection has become an urgent necessity amid increasing maritime activities, including security monitoring, law enforcement, and maritime traffic management. This study aims to implement the Faster R-CNN (Region-based Convolutional Neural Network) method for ship detection to improve efficiency and accuracy compared to conventional methods. The data used in this study consists of 693 ship images. This research also analyzes the performance of the Faster R-CNN method under various image conditions and identifies factors influencing detection performance. The results of this study are expected to make a significant contribution to the development of object detection technology in maritime environments, particularly for security and traffic management applications.

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Availability

Detail Information

Series Title

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Call Number

T1627402024

Publisher

Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2024

Collation

iii, 56 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.650 7

Content Type

Text

Media Type

unmediated

Carrier Type

other (computer)

Edition

-

Subject(s)

Jaringan Komunikasi Komputer
Prodi Sistem Komputer

Specific Detail Info

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Statement of Responsibility

MURZ

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