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Detection of Fairy Circles in UAV Images Using Deep Learning

机译:深入学习检测UAV图像中的童话圈

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Fairy circles are circular patches of barren soil forming large clusters in the arid grasslands of Southern Africa (especially in Namibia) and Western Australia. Fairy circles are clearly visible in aerial images shown in applications such as Google Maps, and they can be recorded using sensors mounted on drones in very high image and video resolution for ecological studies aiming at understanding the origin of these patterns. Traditional analysis of fairy circles is done by manual digitising and counting. We also showed recently that, despite being challenging, traditional computer vision methods enabled the detection of fairy circles. To improve fairy circle detection and localization automatically in aerial images, we here present the use of a convolutional neural network (CNN). The results suggest that new methods using CNNs outperform other methods in terms of accuracy.
机译:童话是荒芜土壤的圆形斑块,在南部非洲干旱的草原(特别是在纳米比亚)和西澳州的群体。在谷歌地图等应用中所示的空中图像中清晰可见,并且可以使用安装在变动上的传感器在非常高的图像和视频分辨率上进行记录,以获得旨在理解这些模式的起源的生态学研究。通过手动数字化和计数完成童话的传统分析。我们还展示了,尽管是具有挑战性的,但传统的计算机视觉方法使得能够检测童话。为了在空中图像中自动改善童话圈检测和本地化,我们在这里介绍了卷积神经网络(CNN)的使用。结果表明,在准确性方面,使用CNNS的新方法优于其他方法。

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