【摘要】在应用型大学中,作为电子信息类研究生,需要主修或选修“数字图像处理”课程,该课程在人工智能领域中占据着重要的地位。根据市场需求和应用型研究生人才培养模式,提出“学生主体、教师主导”的课程建设机制。在教学中,建立“互动、开放”的课堂形式,采用启发式、问题式的教学方法,基于项目提出实际问题,在原有的Matlab软件教学实践的基础上,添加Python 软件,提高学生解决基于人工智能技术的图像处理问题的能力,实现教学案例与实践环节的有效融合。本文对教学内容、教学方法、课程实践、考核体系进行深度剖析,对建设研究生教育数字图像处理优质课程具有重要的意义。
【关键词】数字图像处理 研究生 人工智能 主动学习 创新思维
【Abstract】In applied universities, as a graduate student of electronic information, you need to major or elect the “Digital Image Processing” course, which occupies an important position in the field of artificial intelligence. According to market demand and application-oriented graduate talent training model, a curriculum construction mechanism of “student-oriented and teacher-led” is proposed. In teaching, an “interactive and open” classroom format is established, heuristic and problem-based teaching methods are adopted, actual problems are raised based on the project, Python software is added to the original Matlab software teaching practice to improve students ability to solve image processing problems based on artificial intelligence technology,and realize the effective integration of teaching cases and practical links. This article conducts an in-depth analysis of teaching content, teaching methods, course practice, and assessment system, which is of great significance to the construction of a high-quality course of digital image processing in graduate education.
【Keywords】digital image processing; graduate students; artificial intelligence; active learning; innovative thinking
【基金項目】本文系2020年临沂大学研究生教育优质课程建设项目(YZKC2005)的研究成果。
【中图分类号】G64 【文献标识码】A 【文章编号】2095-3089(2021)08-0186-02
一、引言
近年来,随着人工智能(AI)、深度学习技术和大数据的迅速崛起,数字图像处理技术已被广泛用于工业检测、生物医学、通信、遥感、智能交通等不同的研究领域[1]。数字图像处理作为人工智能大类的课程之一,是一门使用计算机进行分析图像与提取信息的学科,具有交叉性强、实践性和推理性强、内容更新快的特点[2-3]。传统的“数字图像处理”课程教学一般都以教师课堂讲解理论知识为主,实验课上,通过一些小型实验来验证简单的原理,这种教学模式已不能达到培养研究生创新思维及实操能力的目的。……