Zobrazeno 1 - 10 of 699 pro vyhledávání: '"David P. Casasent"'
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Fast feature selection algorithm for poultry skin tumor detection in hyperspectral data
Autor: David P. Casasent, Songyot Nakariyakul
Publikováno v: Journal of Food Engineering. 94:358-365
Hyperspectral reflectance imaging data are analyzed for poultry skin tumor detection. We consider selecting only a few wavebands from hyperspectral data for potential use in a real-time multispectral camera. To do this, we improve our prior tumor det
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f89d8f7abbb087b9a7c583c817bd1b92
https://doi.org/10.1016/j.jfoodeng.2009.04.001
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3
An improvement on floating search algorithms for feature subset selection
Autor: David P. Casasent, Songyot Nakariyakul
Publikováno v: Pattern Recognition. 42:1932-1940
A new improved forward floating selection (IFFS) algorithm for selecting a subset of features is presented. Our proposed algorithm improves the state-of-the-art sequential forward floating selection algorithm. The improvement is to add an additional
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::211aaa19941c6aa29db19f0b8baab689
https://doi.org/10.1016/j.patcog.2008.11.018
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4
Adaptive branch and bound algorithm for selecting optimal features
Autor: David P. Casasent, Songyot Nakariyakul
Publikováno v: Pattern Recognition Letters. 28:1415-1427
We propose a new adaptive branch and bound algorithm for selecting the optimal subset of features in pattern recognition applications. The algorithm improves the search speed by avoiding unnecessary criterion function calculations at nodes in the sol
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cce1ac48b5022db5c1bc01c7385bdb61
https://doi.org/10.1016/j.patrec.2007.02.015
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6
New training strategies for RBF neural networks for X-ray agricultural product inspection
Autor: David P. Casasent, Xue-wen Chen
Publikováno v: Pattern Recognition. 36:535-547
Classification of real-time X-ray images of pistachio nuts is discussed. The goal is to reduce the percentage of infested nuts while not rejecting more than a few percent of the good nuts. Radial basis function (RBF) neural network classifiers are em
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2b97459fc3f0b39897b55234b688c574
https://doi.org/10.1016/s0031-3203(02)00058-4
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7
Feature space trajectory methods for active computer vision
Autor: Michael Andrew Sipe, David P. Casasent
Publikováno v: IEEE Transactions on Pattern Analysis and Machine Intelligence. 24:1634-1643
We advance new active object recognition algorithms that classify rigid objects and estimate their pose from intensity images. Our algorithms automatically detect if the class or pose of an object is ambiguous in a given image, reposition the sensor
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::219e53a0b9a4ee03004b150eeb6031e7
https://doi.org/10.1109/tpami.2002.1114854
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8
Crystallographic Distribution of Low Angle Grain Boundary Planes in Magnesium Oxide
Autor: David M. Saylor, Adam Morawiec, S. Mahadevan, K.W. Cherry, David P. Casasent, F.H. Rogan, Gregory S. Rohrer
Publikováno v: Materials Science Forum. :1705-1710
We have developed a technique that allows all five macroscopically observable grain boundary degrees of freedom to be characterized for a statistically significant number of interfaces. Using this technique, we have characterized 5 x 10 μm of grain
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e82dd2389e99074027dc9b0821e4d96b
https://doi.org/10.4028/www.scientific.net/msf.408-412.1705
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10
A closed-form neural network for discriminatory feature extraction from high-dimensional data
Autor: David P. Casasent, Ashit Talukder
Publikováno v: Neural Networks. 14:1201-1218
We consider a new neural network for data discrimination in pattern recognition applications. We refer to this as a maximum discriminating feature (MDF) neural network. Its weights are obtained in closed-form, thereby overcoming problems associated w
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bc531f9b1fe4010f466c16161f6e7cb4
https://doi.org/10.1016/s0893-6080(01)00103-4
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