基于SE-ResNeXt的昆虫自动识别系统

Yao Xiao, Aocheng Zhou, Lin Zhou, Yue Zhao
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引用次数: 1

摘要

黑龙江省五大连池风景名胜区是世界上研究物种适应和生物群落进化的最佳地点。针对昆虫鉴定工作量大、时效性差、专业性强、准确性低等问题,提出了一种基于SE-ResNeXt的昆虫自动鉴定系统。首先,为了适应五大连池昆虫的研究,数据集采用了五大连池8目昆虫105种的图像。然后,通过三种卷积神经网络的比较,SE-ResNeXt对昆虫的识别准确率高于ResNet和Inception-V4,其召回率、精度、f1评分和准确率均达到98%以上。最后,基于Django框架搭建了系统的网站和app,实现了五大连池昆虫数据的识别结果可视化和数字化存储。该系统具有交互性强、操作方便的特点,旨在为农林昆虫保护、昆虫知识普及提供技术支持,并为中国五大连池昆虫品种的长期进化提供数据基础。
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Automatic insect identification system based on SE-ResNeXt
The Wudalianchi Scenic Area in Heilongjiang Province is the greatest place in the world to study species adaption and the evolution of biological communities. To solve the problems of heavy workload, poor timeliness, strong professionalism, and low accuracy in insect identification, an automatic insect identification system based on SE-ResNeXt is proposed. Firstly, to be suitable for the study of Wudalianchi insects, the dataset adopts the images of 105 species of eight orders insect in Wudalianchi. Then, through the comparison of three convolution neural networks, SE-ResNeXt has higher accuracy of insect identification than ResNet and Inception-V4, and its recall, precision, F1-score and accuracy all reach over 98%. Finally, based on Django framework, the website and app of system are built to realise the visualisation of identification results and the digital storage of insect data in Wudalianchi. The system has the characteristics of strong interactivity and convenient operation, and it was designed to provide technical assistance for insect protection, insect knowledge popularisation in agriculture and forestry, and a data foundation for the long-term evolution of insect variety in Wudalianchi, China.
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来源期刊
International Journal of Systems, Control and Communications
International Journal of Systems, Control and Communications Engineering-Control and Systems Engineering
CiteScore
1.50
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0.00%
发文量
26
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