PEST INFESTATION IDENTIFICATION IN COCONUT TREES USING DEEP LEARNING

Abraham Chandy
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引用次数: 32

Abstract

In this paper, we propose a precision agriculture technique to detect various pests in coconut trees with the help of NVIDIA Tegra System on Chip (SoC) along with a camera interfaced drone. The drone flies across the coconut farm and captures the images and processes the data using deep learning algorithm to identify the unhealthy and pest affected trees. The deep learning algorithm uses a set of sample pest database. The Artificial Intelligence (AI) machine learning algorithm is also capable of unsupervised learning from the images that are unstructured. The data is transferred directly to the farmer’s smart phone with the help of wi-fi. This helps in timely treatment of pest infected trees and to improve the yield of the trees.
利用深度学习识别椰子树害虫
在本文中,我们提出了一种精准农业技术,利用NVIDIA Tegra系统芯片(SoC)和摄像头接口无人机来检测椰树中的各种害虫。无人机飞过椰子农场,捕捉图像,并使用深度学习算法处理数据,以识别不健康和受虫害影响的树木。该深度学习算法使用了一组样本害虫数据库。人工智能(AI)机器学习算法也能够从非结构化的图像中进行无监督学习。数据在wi-fi的帮助下直接传输到农民的智能手机上。这有助于及时处理病虫害的树木,提高树木的产量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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