Klasifikasi Bangun Dua Dimensi Menggunakan YOLOV4 Berbasis Nvidia Jetson Nano pada Smart Whiteboard

Akbar, Ahmad Syiham (2023) Klasifikasi Bangun Dua Dimensi Menggunakan YOLOV4 Berbasis Nvidia Jetson Nano pada Smart Whiteboard. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Tujuan dari penelitian ini adalah membuat alat yang dapat klasifikasi bangun datar dua dimensi pada papan tulis pintar. Bangun datar dua dimensi yang di deteksi adalah persegi, persegi panjang, lingkaran, segitiga, trapesium. Metode yang akan digunakan adalah dengan menggunakan You Only Look Once v4-tiny sebagai framework kerja dalam pembuatan program pendeteksi bangun datar dua dimensi berbasis Nvidia Jetson Nano secara real time. Sistem yang dikembangkan pada penelitian ini berbasis computer vision dengan menggunakan kamera sebagai sensornya secara real time. Secara keseluruhan sistem pendeteksi objek pada penelitian ini berjalan dengan baik. Nvidia Jetson Nano mampu klasifikasi gambar bangun datar dua dimensi pada papan tulis pintar dengan berbagai pengujian menggunakan metode You Only Look Once secara real time.
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The purpose of this study is to create a device that can detect two-dimensional flat shapes on a smart whiteboard. Two-dimensional flat shapes detected are square, rectangle,
circle, triangle, trapezoid. The method that will be used is to use You Only Look Once (YOLO) v4-tiny as a framework for creating a two-dimensional flat wake detection program based on NVIDIA Jetson Nano in real time. The system developed in this study is based on computer vision by using a camera as a sensor in real-time. Overall, the object detection system in this study went well. The Nvidia Jetson Nano is able to detect a two-dimensional flat image on a smart whiteboard with various tests using the You Only Look Once (YOLO) method in real-time.

Item Type: Thesis (Other)
Uncontrolled Keywords: Klasifikasi, Nvidia Jetson Nano, YOLO, Bangun Dua Dimensi, papan Tulis Pintar,Classification, Nvidia Jetson Nano, YOLO, Two-Dimensional, Smart Smart Whiteboard.
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Electrical Technology > Computer Engineering > 90243-(S1) Undergraduate Thesis
Depositing User: Ahmad Syiham Akbar
Date Deposited: 17 Feb 2023 06:42
Last Modified: 20 Feb 2023 02:28
URI: http://repository.its.ac.id/id/eprint/97601

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