基于深度学习的鱼病防治APP教学实践系统设计  

Design of Fish Disease Detection APP Teaching Practice System Based on Deep Learning

作　　者：冼远清[1] 江颖龙 初庆柱 彭小红[1] XIAN Yuanqing;JIANG Yinglong;CHU Qingzhu;PENG Xiaohong(School of Mathematics and Computer,Guangdong Ocean University,Zhanjiang 524088,Guangdong,China;Aquatic Organisms Museum,Guangdong Ocean University,Zhanjiang 524088,Guangdong,China)

机构地区：[1]广东海洋大学数学与计算机学院,广东湛江524088 [2]广东海洋大学水生生物博物馆,广东湛江524088

出　　处：《实验室研究与探索》2024年第3期12-17,共6页Research and Exploration In Laboratory

基　　金：教育部协同育人项目(201902303056);广东海洋大学本科教学质量与教学改革工程(PX52023243);广东海洋大学教学研究与改革项目(XJG202150);湛江市科技攻关计划(2019B01008)。

摘　　要：针对移动编程技术教学方案中缺少与人工智能技术相结合的实验教学内容问题,设计了一个以Android和YOLOv5s为核心技术的鱼病防治教学实践系统。基于成果导向教育理念,将理论知识与科研项目相结合,引入CDIO(conceive(构思)-design(设计)-implement(实现)-operate(运作))教学模式,以系统功能设计、深度学习开发环境搭建、鱼病数据集构建、YOLOv5s鱼病检测算法设计、项目部署与测试、项目答辩路演等为主要教学模块进行递进式实验教学。实践表明,该系统充分调动了学生的主观能动性,培养了学生的创新精神,增强了学生的工程实践能力。Aiming at the problem of lack of experimental teaching content,a fish disease prevention and control teaching practice system with Android and YOLOv5s as the core technology is designed.The system is designed based on the outcomes-based education concept,combines theoretical knowledge with scientific research projects,introduces CDIO(conceive-design-implement-operate)teaching mode,and takes system function design,deep learning development environment construction,fish disease dataset construction,YOLOv5s fish disease detection algorithm design,project deployment and testing,project defense roadshow as the main teaching modules for progressive teaching.Practice shows that the system fully mobilizes students'subjective initiative,cultivates students’innovative spirit,enhances students’engineering practice ability,and greatly improves the teaching effect.

关 键 词：鱼病识别 人工智能 实验教学 深度学习 

分 类 号：G642[文化科学—高等教育学]