Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Scott Philips"'
Autor:
Nasim Zamani, Amirhossein Hosseini, Fariba Farnaghi, Aliakbar Sayyari, Narges Gholami, Farid Imanzadeh, Seyed Kaveh Hadeiy, Mahmoud Hajipour, Amir Salimi, Scott Philips, Hossein Hassanian-Moghaddam
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-7 (2023)
Abstract Constipation is a common reason for children seeking medical care worldwide. Abdominal complaints and constipation are also common in lead-poisoned children. This study evaluates the prevalence of abnormal blood lead levels (BLL) among pedia
Externí odkaz:
https://doaj.org/article/d98215a405614671b90656b3d1850072
A novel unified Bayesian framework for network detection is developed, under which a detection algorithm is derived based on random walks on graphs. The algorithm detects threat networks using partial observations of their activity, and is proved to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::41c698a58d6dc1dc9589b9dbbe3354ab
http://arxiv.org/abs/1311.5552
http://arxiv.org/abs/1311.5552
Publikováno v:
ICASSP
Existing literature on network community detection typically exploits the structure of static associations between entities. However, real world network data often consists of observations of coordinated interactions between members who belong to mul
Publikováno v:
ICASSP
This paper addresses threat propagation on space-time graphs, defined to be a time-sampled graph. The application considered is geographi-cal sites connected by tracks, though such graphs arise in many fields. Several new concepts and efficient algor
Publikováno v:
ICASSP
Dimensionality reduction algorithms have become an indispensable tool for working with high-dimensional data in classification. Linear discriminant analysis (LDA) is a popular analysis technique used to project high-dimensional data into a lower-dime
This research develops a framework for employing perceptual information from human listening experiments to improve automatic event classification. We focus on the identification of new signal attributes, or features, that are able to predict the hum
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2bf6e2be5c035da8ca1077c167159161
https://doi.org/10.21236/ada476810
https://doi.org/10.21236/ada476810
Publikováno v:
OCEANS 2006.
This paper presents a novel method of using psychoacoustic information from human listening experiments to generate useful features for automated signal classification or regression. The design and analysis of a similarity experiment using active son
Autor:
Derek Brock, Maxwell H. Miller, Scott Philips, James W. Pitton, James A. Ballas, Les Atlas, Brian McClimens
Publikováno v:
The Journal of the Acoustical Society of America. 119:3394-3395
The goal of this effort is to develop automatic target classification technology for active sonar systems by exploiting knowledge of signal processing methods and human auditory processing. Using impulsive‐source active sonar data, formal listening
Publikováno v:
The Journal of the Acoustical Society of America. 119:3395-3396
Multidimensional scaling (MDS) listening experiments have long been used to better understand the perceptual cues human use when distinguishing between sounds in a given dataset. By collecting aural similarity measures between sound pairings, one can
Autor:
Scott Philips, James W. Pitton
Publikováno v:
The Journal of the Acoustical Society of America. 123:3344-3344
In many acoustic signal processing applications human listeners are able to outperform automated processing techniques, particularly in the identification and classification of acoustic events. This paper develops a framework for employing perceptual