Moving Image YOLOv3 Process Comparison with Multiple Resolutions and Frames-per-Second-Reference-Cited by-同舟云学术

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Moving Image YOLOv3 Process Comparison with Multiple Resolutions and Frames-per-Second

Published:2022-07-20 Issue: Volume: Page:
ISSN:
Container-title:2022 International Seminar on Intelligent Technology and Its Applications (ISITIA)
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Author:

Al-Azam Moh Noor¹,Achlaq Mochamad Mizanul²,Darujati Cahyo³

Affiliation:

1. Program Studi Teknik Informatika Fakultas Teknik dan Ilmu Komputer Universitas Narotama,Surabaya,Indonesia

2. Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer Universitas Narotama,Surabaya,Indonesia

3. Program Studi Sistem Komputer Fakultas Teknik dan Ilmu Komputer Universitas Narotama,Surabaya,Indonesia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9855197/9855201/09855267.pdf?arnumber=9855267

Reference24 articles.

1. Understanding How Video Quality Affects Object Detection Algorithms

2. Image quality and super resolution effects on object recognition using deep neural networks

3. The Excellent Properties of a Dense Grid-Based HOG Feature on Face Recognition Compared to Gabor and LBP

4. Vehicle detection using simplified fast R-CNN

5. Cascade R-CNN: Delving Into High Quality Object Detection

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. AFAR-YOLO: An Adaptive YOLO Object Detection Framework;2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS);2024-01-28

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