Simplification of Image Segmentation and Object Detection Teaching Materials

Ziga Emersic, Gregor Hrastnik, Natasa Meh Peer, Vasja Lev Kirn, Aljaz Justin, Jovana Videnovic, Luka Markicevic, Peter Peer

Abstract: The recent quick progress in artificial intelligence including deep learning in computer vision, opened the need for early AI education in schools. This paper presents the creation of a computer vision curriculum as a part of AIM@VET (Artificial Intelligence Modules for Vocational Education and Training) EU project for different levels of students with emphasis on pre-university students and teacher’s feedback that served as a feedback loop for the development of the materials. Moreover, the pre-feedback materials that proved to be too challenging for pre-university students were forked into additional version for early university students. The course material is available in traditional formats and Python notebooks, integrating theoretical concepts with practical coding exercises. Both teacher and student versions are provided, utilizing interactive tools and open-source libraries for hands-on learning.

External IDs:dblp:conf/ideal/EmersicHPKJVMP24