利用航空和街景图像自动大范围检测红棕象甲
Automatic Large Scale Detection of Red Palm Weevil Infestation using Aerial and Street View Images
摘要：
红棕榈象鼻虫的蔓延极大地影响了枣种植者、房主和政府，迫使他们应对棕榈树不断受到的威胁。棕榈树虫害的早期检测已被证明是至关重要的，以允许治疗，可能会挽救树木不可逆转的损害，最常见的是通过当地的物理访问进行个别树木监测。在这里，我们提出了一种新的方法，利用最先进的深度学习算法，利用空中和街道级的图像数据来监视红棕榈象鼻虫出没的棕榈树。为了检测受感染的棕榈树，我们分析了超过10万张空中和街道图像，绘制了棕榈树在城市地区的位置。使用这个程序，我们发现并验证了在不同位置的受感染的棕榈树。
英文摘要：
The spread of the Red Palm Weevil has dramatically affected date growers, homeowners and governments, forcing them to deal with a constant threat to their palm trees. Early detection of palm tree infestation has been proven to be critical in order to allow treatment that may save trees from irreversible damage, and is most commonly performed by local physical access for individual tree monitoring. Here, we present a novel method for surveillance of Red Palm Weevil infested palm trees utilizing state-of-the-art deep learning algorithms, with aerial and street-level imagery data. To detect infested palm trees we analyzed over 100,000 aerial and street-images, mapping the location of palm trees in urban areas. Using this procedure, we discovered and verified infested palm trees at various locations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
