PERBAIKAN KUALITAS PADA CITRA GELAP MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK (CNN)

PUTRI, SALSABILA NABRIMA and Supardi, Julian and Rodiah, Desty (2023) PERBAIKAN KUALITAS PADA CITRA GELAP MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK (CNN). Undergraduate thesis, Sriwijaya University.

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Abstract

Citra gelap atau yang berkontras rendah serta citra yang memiliki objek tidak jelas menyebabkan objek pada citra sulit diidentifikasi baik secara sistem ataupun oleh pengamat. Dalam penelitian ini dilakukan perbaikan citra menggunakan metode Convolutional Neural Network (CNN). Berdasarka hasil penelitian ini menunjukkan hasil yang dikeluarkan oleh sistem tersebut berupa gambar yang sudah diperbaikai yaitu gambar citra terang. Data yang digunakan memperoleh nilai PSNR dan nilai SSIM. Nilai rata-rata PSNR adalah 81.66438 dan nilairata-rata SSIM adalah 0.150688.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Citra Gelap, Convolutional Neural Network (CNN), PSNR, SSIM.
Subjects:	T Technology > T Technology (General) > T58.5-58.64 Information technology > T58.5 General works Management information systems Cf. HD30.213 Industrial management Cf. HF5549.5.C6+ Communication in personnel management Cf. TS158.6 Automatic data collection systems (Production control)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Salsabila Nabrima Putri
Date Deposited:	19 May 2023 08:01
Last Modified:	19 May 2023 08:01
URI:	http://repository.unsri.ac.id/id/eprint/104033

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