NSF Award
2205578
The Historically Black Colleges and Universities (HBCU) Undergraduate Program’s Targeted Infusion Projects aim to support research and educational projects to improve the success of HBCU students in science, technology, engineering or mathematics (STEM) graduate programs and careers. Computer vision is an important subfield of artificial intelligence, and it deals with developing and analyzing algorithms that can extract useful information from images. Its origins can be traced to research activities in the 1960s aiming to invent machines that imitate human cognitive functions in directly observing information from photos. Since computer vision is instrumental in science and technology, this targeted infusion project focuses on advancing this field by improving curriculum and establishing new educational and research infrastructures at Texas Southern University. <br/><br/>Learning computer vision theories can be challenging for most undergraduate students as these theories often involve high levels of mathematical relations. A common way of teaching computer vision is to present theoretical foundations that are followed by examples to highlight the significance of these theories. However, students may have difficulties following lengthy mathematical derivations and understanding specific rationales of these derivations without seeing examples that clarify the role of major components. In order to improve teaching methodology in computer vision, this project aims to implement and investigate two teaching models, based on theoretical and hands-on exposure to computer vision. The other aims of this project are to create a computer vision certification program including a new course on this field at Texas Southern University, to create a computer vision research program to engage senior year undergraduate students in research, and to provide educational and research opportunities to high school students in computer vision through summer boot camps. To this end, learning modules with theoretical and laboratory components to strengthen students' knowledge and practical skills, computational resources, and continuous supervision for their research projects are provided.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
