摘要
本文从应用型人才培养的角度,以实际工程背景的实践案例来促进机器学习课程的教学效果。在机器学习课程实践教学中引入矿山生产中矿石图像粒度分级任务的工程实际需求,设计运用机器学习中的深度学习技术实现矿石图像识别进行教学实验,从而达到提高分类效率和准确率的目的。
From the perspective of application-oriented personnel training,this paper uses practical cases with practical engineering background to promote the teaching effect of machine learning course.In the practical teaching of machine learning course,the practical needs of the task of ore image granularity classification in mine production are introduced,and the deep learning technology in machine learning is designed to realize the ore image recognition for teaching experiments,so as to improve the classification efficiency and accuracy.
作者
栗辉
蔡铮
郭立晴
张皓玥
么增琨
Li Hui;Cai Zheng;Guo Liqing;Zhang Haoyue;Yao Zengkun(School of Automation and Electrical Engineering,University of Science and Technology Beijing,Beijing,100083;School of Computer and Communication Engineering,University of Science and Technology Beijing,Beijing,100083)
出处
《电子测试》
2020年第8期130-131,共2页
Electronic Test
基金
北京科技大学教育教学改革与研究面上项目(JG2017M25)。
关键词
深度学习
实践教学
图像分类
deep learning
practical teaching
image classification
