基于深度学习的农作物病虫害识别研究进展
摘要： 为了对农作物病虫害进行有效防治、有效保障农作物健康状况,快速、精准地识别农作物病虫害是有效防治的前提条件。对农作物病虫害识别研究进行了综述,归纳了农作物病虫害识别方法的发展历程,重点分析了深度学习的网络结构、建模重点环节及6类典型架构特征,并结合当下的研究热点和应用前景,从构建公共数据集、集成多种成像技术、优化大模型性能等方向进行展望。
关键词: 深度学习, 农作物病虫害, 图像识别, 有效防治
Abstract: In order to effectively prevent and control crop diseases and pests, and ensure crop health, rapid and accurate identification of crop diseases and pests was a prerequisite for effective prevention and control.A review was conducted on the research on crop pest and disease identification, summarizing the development process of crop pest and disease identification methods. The focus was on analyzing the network structure, modeling key links, and six typical architectural features of deep learning. Combined with current research hotspots and application prospects, prospects were made from the construction of public datasets, integration of multiple imaging technologies, and optimization of large model performance.
Key words: deep learning, crop diseases and pests, image recognition, effective prevention and control
中图分类号:
S126
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