准科研模式的计算机视觉实验课程建设
Computer vision experimental course construction base on quasi-scientific research mode
付海燕 1李祎 2李华龙 1展金1
作者信息
- 1. 大连理工大学 信息技术实验中心
- 2. 大连理工大学 人工智能学院, 辽宁 大连 116023
- 折叠
摘要
人工智能"新工科"建设强调对学生实践能力、学科交叉能力、团队协作能力、创新能力的培养.计算机视觉实验作为人工智能专业的核心专业实验课,从科研项目中提炼能够反映前沿性和创新性的有挑战度的实验内容,采用多路径迭代的实验设计,通过准科研的过程体验,将学生的知识、能力和素质培养进行有机融合,实现从单科到交叉、从被动到主动、从应试到实战、从个体到协作的四个转变,培养学生解决复杂工程问题的能力和科研创新能力.
Abstract
The construction of artificial intelligence"new engineering"emphasizes the cultivation of students'practical ability,disciplinary interdisciplinary ability,team collaboration ability and innova-tion ability.As the core professional experimental course of artificial intelligence,computer vision ex-periment extracts challenging contents from scientific research projects,which can reflect the frontier and innovation.The experimental design of multi-path iteration is adopted to organically integrate students'knowledge,ability and quality training.This process can make students achieve four changes from single subject to cross,from passive to active,from exam-oriented to actual combat,from indi-vidual to collaboration.Finally,students'ability to solve complex engineering problems and scientific research innovation are cultivated.
关键词
计算机视觉/准科研模式/人工智能专业/实验课程建设Key words
computer vision/quasi-scientific research mode/artificial intelligence/experimental course construction引用本文复制引用
基金项目
国家自然科学基金(62076052)
国家自然科学基金(62106037)
教育部新工科研究与实践项目(第二批)(E-RGZN20201014)
辽宁省普通高等教育本科教学改革研究一般项目(2022)(20221014140)
出版年
2024
NETL
NSTL
万方数据