Targeted Infusion Project: Advancing Basic Science Research and Undergraduate Education in Computer Vision

历史上的黑人学院和大学（HBCU）本科项目的目标注入项目旨在支持研究和教育项目，以提高HBCU学生在科学、技术、工程或数学（STEM）研究生课程和职业生涯中的成功。计算机视觉是人工智能的一个重要分支，它涉及开发和分析可以从图像中提取有用信息的算法。它的起源可以追溯到20世纪60年代的研究活动，目的是发明模仿人类直接观察照片信息的认知功能的机器。由于计算机视觉在科学和技术中发挥着重要作用，这个有针对性的注入项目将重点放在通过改进课程和在德克萨斯南方大学建立新的教育和研究基础设施来推进这一领域。学习计算机视觉理论对大多数本科生来说是具有挑战性的，因为这些理论通常涉及高水平的数学关系。计算机视觉教学的一种常见方法是先介绍理论基础，然后用例子来突出这些理论的重要性。然而，如果没有看到阐明主要组成部分作用的例子，学生可能会在冗长的数学推导和理解这些推导的具体原理方面遇到困难。为了改进计算机视觉的教学方法，本项目旨在实施和研究两种教学模式，基于理论和实践接触计算机视觉。该项目的另一个目标是创建一个计算机视觉认证项目，包括在德克萨斯南方大学开设该领域的新课程，创建一个计算机视觉研究项目，让大四的本科生参与研究，并通过暑期训练营为高中学生提供计算机视觉方面的教育和研究机会。为此，提供理论和实验组成的学习模块，以加强学生的知识和实践技能，计算资源，并为他们的研究项目提供持续的监督。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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. 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.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.