复杂场景下害虫目标检测算法:YOLOv8-ExtendOACSTPCD
Crop Pest Target Detection Algorithm in Complex Scenes:YOLOv8-Extend
[目的/意义]实现复杂的自然环境下农作物害虫的识别检测,改变当前农业生产过程中依赖于专家人工感官识别判定的现状,提升害虫检测效率和准确率具有重要意义.针对农作物害虫目标检测具有目标小、与农作物拟态、检测准确率低、算法推理速度慢等问题,本研究提出一种基于改进YOLOv8的复杂场景下农作物害虫目标检测算法.[方法]首先通过引入GSConv提高模型的感受野,部分Conv更换为轻量化的幻影卷积(Ghost Convo-lution),采用HorBlock…查看全部>>
[Objective]It is of great significance to improve the efficiency and accuracy of crop pest detection in complex natural environments,and to change the current reliance on expert manual identification in the agricultural production process.Targeting the problems of small target size,mimicry with crops,low detection accuracy,and slow algorithm reasoning speed in crop pest detection,a complex scene crop pest target detection algorithm named YOLOv8-Entend was pr…查看全部>>
张荣华;白雪;樊江川
京航创智(北京)科技有限公司,北京 102404,中国京航创智(北京)科技有限公司,北京 102404,中国国家农业信息化工程技术研究中心,北京 100097,中国||数字植物北京市重点实验室,北京 100097,中国
植物保护学
YOLOv8害虫检测注意力机制边缘计算CBAMBiFPNVoVGSCSPGSConv
YOLOv8pest detectionattention mechanismedge computingCBAMBiFPNVoVGSCSPGSConv
《智慧农业（中英文）》 2024 (2)
49-61,13
北京市科技新星计划(Z211100002121065,Z20220484202)"十四五"国家重点研发计划项目(2022YFD2002302-02) Beijing Nova Program(Z211100002121065,Z20220484202)National Key Research and Development Program(2022YFD2002302-02)
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