现代农业科技Issue(13)：164-167,169,5.
基于YOLO v2的莲蓬快速识别研究
Research on Lotus Quick Recognition Based on YOLO v2
摘要
Abstract
Affected by the shape and growth environment of lotus,the traditional computer vision algorithm has the problems of poor efficiency and precision.In this paper,the scheme of using YOLO v2 algorithm to recognize the lotus was proposed.Through expanding lotus detection data set,K-means dimension clustering,depthwise separable convolution network,multi-scale classified network fine-tuning and other methods to improve the recognition accuracy,robustness and recognition speed.Contrasting the actual performance of Darknet-19,Tiny Darknet and DS Tiny Darknet with the YOLO v2 algorithm,the results showed that the scheme could achieve the recognition rate of 102.1 fps,realize the quick recognition of the lotus in a complex environment,so as to meet the realtime vision demand for picking robot in picking process.关键词
莲蓬/识别/YOLO v2/深度学习/目标检测/模型加速Key words
lotus/recognition/YOLO v2/deep learning/object detection/model acceleration分类
信息技术与安全科学引用本文复制引用
黄小杭,梁智豪,何子俊,黄晨华,李湘勤..基于YOLO v2的莲蓬快速识别研究[J].现代农业科技,2018,(13):164-167,169,5.基金项目
2017年地方高校国家级大学生创新创业训练计划项目(201710576005) （201710576005）
广东省大学生科技创新培育专项资金(pdjha0 452). （pdjha0 452）
