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Real-time Localization of Hard Corals in Underwater Videos Using Darknet-YOLO Network

سال انتشار: 1399
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 386

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شناسه ملی سند علمی:

CEITCONF04_023

تاریخ نمایه سازی: 13 تیر 1400

چکیده مقاله Real-time Localization of Hard Corals in Underwater Videos Using Darknet-YOLO Network

Real-time identifying and classifying hard corals on underwater videos is a critical task to cost-effectively monitor hard corals localization. In this work, we address the problem, using darknet-YOLO framework. To this end, twenty-four convolutional layers of Darknet-YOLO is employed to detect a single hard coral class. The detection and localization method repeated on each video’s frame. To evaluated the framework performance, a collection of coral images has been extracted from the video and tagged manually. The collection consist 10000 sequential images and hard corals’ location are extracted on each frame. The system achieves approximately 88.3% on recall and 88.8% on accuracy.

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نویسندگان مقاله Real-time Localization of Hard Corals in Underwater Videos Using Darknet-YOLO Network

Pargol Ghavam Mostafavi

Department of Marine Sciences, Science and Research branch, Islamic Azad University Tehran, Iran

Kambiz Rahbar

Department of Computer Engineering, South Tehran Branch, Islamic Azad University Tehran, Iran

Anis Rahati

Department of Computer Engineering, South Tehran Branch, Islamic Azad University Tehran, Iran

Abbass Ghadami-Yazdi

Department of Marine Sciences, Science and Research branch, Islamic Azad University Tehran, Iran