Matthew N. Dailey, Ph.D.

University of California, San Diego, La Jolla, CA 
Computational Cognitive Neuroscience
"Matthew Dailey"
Mean distance: 15.84 (cluster 29)


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Garrison Cottrell grad student 2002 UCSD
 (Computational models of high-level visual perception and recognition.)


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Michael Lyons collaborator UCSD
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Rhienmora P, Haddawy P, Suebnukarn S, et al. (2015) Recognizing Clinical Styles in a Dental Surgery Simulator. Studies in Health Technology and Informatics. 216: 163-7
Noor W, Dailey MN, Haddawy P. (2014) Learning predictive choice models for decision optimization Ieee Transactions On Knowledge and Data Engineering. 26: 1932-1945
Iqbal W, Dailey MN, Carrera D. (2014) Low cost quality aware multi-tier application hosting on the amazon cloud Proceedings - 2014 International Conference On Future Internet of Things and Cloud, Ficloud 2014. 202-209
Teeravech K, Nagai M, Honda K, et al. (2014) Discovering repetitive patterns in facade images using a RANSAC-style algorithm Isprs Journal of Photogrammetry and Remote Sensing. 92: 38-53
Baber J, Dailey MN, Satoh S, et al. (2014) BIG-OH: BInarization of gradient orientation histograms Image and Vision Computing. 32: 940-953
Rhienmora P, Haddawy P, Suebnukarn S, et al. (2011) Intelligent dental training simulator with objective skill assessment and feedback. Artificial Intelligence in Medicine. 52: 115-21
Baber J, Afzulpurkar N, Dailey MN, et al. (2011) Shot boundary detection from videos using entropy and local descriptor 17th Dsp 2011 International Conference On Digital Signal Processing, Proceedings
Iqbal W, Dailey MN, Carrera D. (2011) Black-box approach to capacity identification for multi-tier applications hosted on virtualized platforms Proceedings - 2011 International Conference On Cloud and Service Computing, Csc 2011. 111-117
Iqbal W, Dailey MN, Carrera D, et al. (2011) Adaptive resource provisioning for read intensive multi-tier applications in the cloud Future Generation Computer Systems. 27: 871-879
Dailey MN, Joyce C, Lyons MJ, et al. (2010) Evidence and a computational explanation of cultural differences in facial expression recognition. Emotion (Washington, D.C.). 10: 874-93
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