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Sea Turtle Detection Using Faster R-CNN for Conservation Purpose

机译:海龟使用更快的R-CNN进行保护用途

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摘要

Automatically monitoring see turtles over extensive coastlines is an important task for environmental research and conservation nowadays. Unfortunately, some of the sea turtle species have become endangered today and this is why there is a need for search-and-rescue. Computer vision algorithms can be used for sea turtle detection and monitoring. Recently, due to the powerful Convolutional Neural Networks (CNNs), computer vision crucial applications came to reality. Although such algorithms are computationally expensive, they have proved promising results where real-time applications can be feasibly implemented given high-capability GPUs. In this paper, we present a system of sea turtles detection using a Faster R-CNN algorithm. This system performs the sea turtles' detection on a cloud (off-board). Our detection algorithm can be performed using a static camera, or a moving camera that is mounted on UAVs for surveillance, search-and-rescue purposes.
机译:自动监测在广泛的海岸线上看到乌龟是现在的环境研究和保护的重要任务。不幸的是,一些海龟物种今天濒临灭绝,这就是为什么需要搜查和救援。计算机视觉算法可用于海龟检测和监测。最近,由于强大的卷积神经网络(CNNS),计算机视觉至关重要的应用程序实现了现实。虽然这种算法是计算昂贵的,但是他们已经证明了有希望的结果,其中可以在给定高能GPUS的实时应用程序中可用实时应用。在本文中,我们使用更快的R-CNN算法提供了一种海龟检测系统。该系统在云(脱机)上执行海龟的检测。我们的检测算法可以使用静态摄像机或移动相机,或者安装在UAV上的监视,搜索和救援目的。

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