Zobrazeno 1 - 10
of 188
pro vyhledávání: '"Glenn Healey"'
Autor:
Glenn Healey, Lequan Wang
Publikováno v:
IEEE Access, Vol 9, Pp 132468-132479 (2021)
We develop a new method for characterizing the lift force on a baseball. The methodology addresses this task from the novel perspective of considering a large set of radar measurements acquired outside of a laboratory setting. The reduced degree of s
Externí odkaz:
https://doaj.org/article/8b442279e3b24a7a96eb20fad4b56126
Autor:
Glenn Healey, Shiyuan Zhao
Publikováno v:
IEEE Access, Vol 9, Pp 137419-137429 (2021)
An important and challenging problem in the evaluation of baseball players is the quantification of batted-ball talent. This problem has traditionally been addressed using linear regression or machine learning methods. We use large sets of trajectory
Externí odkaz:
https://doaj.org/article/9ae946973a2f47da8b3e036a5bc8da35
Autor:
Glenn Healey, Shiyuan Zhao
Publikováno v:
IEEE Access, Vol 8, Pp 172196-172203 (2020)
We present a method for learning a function over distributions. The method is based on generalizing nonparametric kernel regression by using the earth mover's distance as a metric for distribution space. The technique is applied to the problem of lea
Externí odkaz:
https://doaj.org/article/d8acc3ec6f21446c98a638dfe8a2b2f8
Autor:
Glenn Healey
Publikováno v:
IEEE Access, Vol 5, Pp 13811-13822 (2017)
We present a multidisciplinary approach for learning, visualizing, and assessing a model for the intrinsic value of a batted ball in baseball. The new methodology addresses one of the most fundamental problems in baseball analytics. Traditional outco
Externí odkaz:
https://doaj.org/article/fac5c40b2f3c416ebf4f0f271eadde7e
Autor:
Glenn Healey
Publikováno v:
Sensors, Vol 21, Iss 1, p 64 (2020)
Evaluating a player’s talent level based on batted balls is one of the most important and difficult tasks facing baseball analysts. An array of sensors has been installed in Major League Baseball stadiums that capture seven terabytes of data during
Externí odkaz:
https://doaj.org/article/ad8360a143384a35a56c877ead85c296
Comparison of Spectral-Only and Spectral/Spatial Face Recognition for Personal Identity Verification
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2009 (2009)
Face recognition based on spatial features has been widely used for personal identity verification for security-related applications. Recently, near-infrared spectral reflectance properties of local facial regions have been shown to be sufficient dis
Externí odkaz:
https://doaj.org/article/97ef5d1d2e0241af9420506637d8151e
Autor:
Shiyuan Zhao, Glenn Healey
Publikováno v:
IEEE Access, Vol 8, Pp 172196-172203 (2020)
We present a method for learning a function over distributions. The method is based on generalizing nonparametric kernel regression by using the earth mover’s distance as a metric for distribution space. The technique is applied to the problem of l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::788d54320467cec0370022798180d4b1
https://ieeexplore.ieee.org/document/9200448/
https://ieeexplore.ieee.org/document/9200448/
Autor:
Glenn Healey, Han Wang
Publikováno v:
Journal of Computer Sciences and Applications. 7:21-30
Illumination-invariant face recognition remains a challenging problem. Previous studies use either spatial or spectral information to address this problem. In this paper, we propose an algorithm that uses spatial and spectral information simultaneous
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bdfce48455591e0f263580d7ef85bdef
https://doi.org/10.12691/jcsa-7-1-4
https://doi.org/10.12691/jcsa-7-1-4
Autor:
Glenn Healey
Publikováno v:
Journal of Quantitative Analysis in Sports. 15:59-74
The deployment of sensors that characterize the trajectory of pitches and batted balls in three dimensions provides the opportunity to assign an intrinsic value to a pitch that depends on its physical properties and not on its observed outcome. We ex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b4984d2e20b71f93f3c152d6feab8e3b
https://doi.org/10.1515/jqas-2017-0058
https://doi.org/10.1515/jqas-2017-0058
Autor:
Glenn Healey
Publikováno v:
Proceedings of the IEEE. 105:1999-2002
Advancements in the capability of sensors, processors, and storage devices have led to an explosion in the amount of data that is captured during sporting events. The Statcast system, for example, uses Doppler radar and stereoscopic video from two ar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1728808c6324230e8cad2c1caf94732b
https://doi.org/10.1109/jproc.2017.2756740
https://doi.org/10.1109/jproc.2017.2756740