【摘要】 开发了一种基于手机的便携式藻类显微与智能识别系统，可实现水体中微藻种类和密度的现场检测。显微装置借助手机相机模块获取藻类显微图像，基于yolov5目标检测模型设计一款手机APP,调用手机拍摄的微藻显微照片进行目标藻类的识别与分析，经过训练和学习，其识别精确率可达0.94。在梯度实验中，便携式显微镜视场可见微藻数量与微藻密度有较好的线性相关性，R~2为0.979。实验结果表明，该系统可以实现水体中微藻的现场检测和水华监测，为监测水华发展状况、水华预警和微藻研究等提供支撑。更多还原

【Abstract】 A portable microscopic and intelligent identification system based on mobile phone is developed for detecting the microalgae species and density in water on-site. The algae microscopic images is first obtained through the mobile camera module, and then a mobile app based on yolov5 target detection model is designed to identify and analyze the target algae. After training and learning, the recognition precision is able to reach 0.94. In the gradient experiment, the number of microalgae visible in the view field of portable microscope shows good linear correlation with microalgae density with the R~2 of 0.979. The experimental results show that the system can realize the detection of microalgae and water bloom monitoring on-site, and provide support for relevant studies, such as monitoring the development of water bloom, water bloom early warning and microalgae research.更多还原