Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Sethi, Ricky J."'
Autor:
Courchaine, Charles, Sethi, Ricky J.
This foundational research provides additional support for using the Fuzzy ARTMAP neural network as a classification algorithm in the TAR domain. While research opportunities exist to improve recall performance and explanation, the robust recall resu
Externí odkaz:
http://arxiv.org/abs/2305.04237
Autor:
De Veaux, Richard, Agarwal, Mahesh, Averett, Maia, Baumer, Benjamin, Bray, Andrew, Bressoud, Thomas, Bryant, Lance, Cheng, Lei, Francis, Amanda, Gould, Robert, Kim, Albert Y., Kretchmar, Matt, Lu, Qin, Moskol, Ann, Nolan, Deborah, Pelayo, Roberto, Raleigh, Sean, Sethi, Ricky J., Sondjaja, Mutiara, Tiruviluamala, Neelesh, Uhlig, Paul, Washington, Talitha, Wesley, Curtis, White, David, Ye, Ping
Publikováno v:
Annual Review of Statistics, Volume 4 (2017), 15-30
The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for undergraduate programs in Data Science. The group consisted of 25 undergraduate faculty from a variety of institutions in th
Externí odkaz:
http://arxiv.org/abs/1801.06814
Publikováno v:
Intelligent Support for Learning in Groups at International Conference on Intelligent Tutoring Systems (ITS) 2012
In this paper, we present a set of measures to quantify certain properties of threaded discussions, which are ubiquitous in online learn-ing platforms. In particular, we address how to measure the redundancy of posts, the compactness of topics, and t
Externí odkaz:
http://arxiv.org/abs/1702.01873
Publikováno v:
PLoS ONE. Feb2015, Vol. 10 Issue 2, p1-19. 19p.
Akademický článek
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Publikováno v:
In Pattern Recognition Letters 1 November 2013 34(15):2023-2032
Autor:
Sethi, Ricky J.
Publikováno v:
Sethi, Ricky J.(2009). A Physics-Based, Neurobiologically-Inspired Stochastic Framework for Activity Recognition. UC Riverside: Computer Science. Retrieved from: http://www.escholarship.org/uc/item/94g7x701
We present a multi-disciplinary framework for motion modeling and recognition in machine vision. Building upon the neurobiological model of motion recognition, we propose computational equivalents for the Motion Energy and Form Pathways. We derive th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______325::cd57c5047f259ca86312aba85836b644
http://n2t.net/ark:/13030/m5pr7zw2
http://n2t.net/ark:/13030/m5pr7zw2
Akademický článek
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Autor:
De Veaux, Richard D., Agarwal, Mahesh, Averett, Maia, Baumer, Benjamin S., Bray, Andrew, Bressoud, Thomas C., Bryant, Lance, Cheng, Lei Z., Francis, Amanda, Gould, Robert, Kim, Albert Y., Kretchmar, Matt, Lu, Qin, Moskol, Ann, Nolan, Deborah, Pelayo, Roberto, Raleigh, Sean, Sethi, Ricky J., Sondjaja, Mutiara, Tiruviluamala, Neelesh
Publikováno v:
Annual Review of Statistics & Its Application; Mar2017, Vol. 4, p15-30, 11p
Autor:
Sethi, Ricky J.
Publikováno v:
2015 IEEE International Conference on Image Processing (ICIP); 2015, p2925-2929, 5p