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华月珊1, 王佳新2, 戎洁庆2, 华国栋2, 李莉2
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1.广州市辰景生态技术服务有限责任公司;2.河北工程大学
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摘要: |
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随着人工智能的发展，视觉感知技术为林业害虫识别防治提供了新方法和实现思路。论文提出一种基于深度感知神经网络框架实现小蠢虫的检测识别，检测系统具体采用了特征金字塔结构、形变结构和新型非极大值抑制技术进行构建，其准确率达到了96.32%。这说明了基于人工智能技术方案识别林业害虫的可行性。与传统方法相比，此方法在精准识别林业害虫的同时，有效减少不必要的资源消耗。
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关键词:
林业病虫害；小蠢虫检测识别；深度神经网络
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DOI：
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分类号：
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基金项目：邯郸市科学技术研究与发展计划项目(1721203049-1) |
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Research on Scolytidae Recognition and Identification based on ResNet Network |
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huayueshan1, Wang Jiaxin2, Rong Jieqing2, Hua Guodong2, Li Li2
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1.Guangzhou Chenjing Ecological Technology Service Co., Ltd;2.School of Information and Electrical Engineering, Hebei University of Engineering
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Abstract: |
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With the development of artificial intelligence, vision perception technology provides new
methods and implementation ideas for the control of forest pests. In this paper, a forest pest identification
framework based on depth perception neural network is proposed to detect and identify Scolytidae . The detection
system contains feature pyramid structure, deformable convolution structure and non maximum suppression,
which the pest identification model is 96.32%. Compared with traditional methods, this method can accurately
identify forest pests and effectively reduce the consumption of unnecessary resources.
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Key words:
forest diseases and insect pests；Scolytidae recognition and identification；depth neural network
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