Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Obiomon, Pamela"'
AI fairness seeks to improve the transparency and explainability of AI systems by ensuring that their outcomes genuinely reflect the best interests of users. Data augmentation, which involves generating synthetic data from existing datasets, has gain
Externí odkaz:
http://arxiv.org/abs/2410.15470
Personalized adaptive learning (PAL) stands out by closely monitoring individual students' progress and tailoring their learning paths to their unique knowledge and needs. A crucial technique for effective PAL implementation is knowledge tracing, whi
Externí odkaz:
http://arxiv.org/abs/2410.13876
Fairness AI aims to detect and alleviate bias across the entire AI development life cycle, encompassing data curation, modeling, evaluation, and deployment-a pivotal aspect of ethical AI implementation. Addressing data bias, particularly concerning s
Externí odkaz:
http://arxiv.org/abs/2312.12560
Image segmentation is a very popular and important task in computer vision. In this paper, inverse quantum Fourier transform (IQFT) for image segmentation has been explored and a novel IQFT-inspired algorithm is proposed and implemented by leveraging
Externí odkaz:
http://arxiv.org/abs/2301.04705
Autor:
Obiomon, Pamela
Publikováno v:
US Black Engineer and Information Technology, 2020 Dec 01. 44(4), 72-73.
Externí odkaz:
https://www.jstor.org/stable/48634895
Akademický článek
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Akademický článek
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Autor:
Preuss, Michael, Merriweather, Samuel, Avila, John, Butler-Purry, Karen, Watson, Karan, Walton, Shannon, Obiomon, Pamela, Pezold, Frank, Murry, Jasmine, Roth, Michele, Kelley, Judy, Lamm, Harriet
Publikováno v:
Frontiers in Education. 7
In 1991, the Texas A&M University System was one of the first six Louis Stokes Alliance for Minority Participation (LSAMP) awardees. In the three decades of programming, several high impact practices (HIP) have been emphasized. One of them, undergrad
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::01e89aca318c8b9df513cc7cec782bba
https://doi.org/10.3389/feduc.2022.674761
https://doi.org/10.3389/feduc.2022.674761
Publikováno v:
Proceedings of the ASEE Annual Conference & Exposition; 2017, p10456-10467, 12p