Image Recognition Technology in Pest Control Based on Convolution Neural Network and An Improved VGG-16 Algorithm : A Case Stduy of Asian Gaint Hornet

Guangzhe Wang, Qiaoying Bo
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引用次数: 1

Abstract

Since the first witness of a cluster of Asian giant hornet in Canada, the Asian giant hornet, which is also called Vespa mandarinia, has caused serious ecological problems. Therefore, in order to detect Asian giant hornet and collect sighting reports from witnesses, the state of Washington has created a website for people to submit their reports. However, most reported sightings mistake other hornets for the Vespa mandarinia. In order to Identify the image of Vespa mandarinia efficiently, based on convolution neural network, we introduced an improved VGG-16 algorithm to solve the problem. By comparing the results of two experiments, the accuracy of treatment group is better than control group.
基于卷积神经网络和改进VGG-16算法的害虫防治图像识别技术——以亚洲大黄蜂为例
自从第一次在加拿大看到亚洲大黄蜂群以来,亚洲大黄蜂,也被称为Vespa mandarinia,已经造成了严重的生态问题。因此,为了发现亚洲大黄蜂并收集目击者的目击报告,华盛顿州创建了一个网站,供人们提交报告。然而,大多数报道的目击事件都将其他大黄蜂误认为是大黄蜂。为了有效地识别柑橘的图像,在卷积神经网络的基础上,引入了一种改进的VGG-16算法来解决这一问题。对比两组实验结果,治疗组的准确性优于对照组。
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