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Updated: Sep 17, 2025

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus
05:57

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Published on: April 8, 2019

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智能可访问性的先进物体检测:一个Yolov10与海洋捕食者算法,以帮助视力障碍者

Mahir Mohammed Sharif Adam1, Hussah Nasser AlEisa2, Samah Al Zanin3,4

  • 1Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University, AlKharj, Saudi Arabia. m.adam@psau.edu.sa.

Scientific reports
|July 2, 2025
PubMed
概括

本研究引入了一种使用先进的深度学习和海洋捕食者算法 (MPA) 的新物体检测模型,以提高视力障碍者的独立性. 该模型在检测物体方面达到99.63%的准确性,大大提高了可访问性.

关键词:
海洋捕食者算法 海洋捕食者算法对象检测检测对象检测对象检测智能可访问性 智能可访问性视觉障碍的人 视觉障碍的人这就是YOLOv10的意义.

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