Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Timothy J. Draelos"'
Publikováno v:
Seismological Research Letters. 92:388-395
The impressive performance that deep neural networks demonstrate on a range of seismic monitoring tasks depends largely on the availability of event catalogs that have been manually curated over many years or decades. However, the quality, duration,
Publikováno v:
Geophysical Research Letters. 46:3643-3651
Autor:
Christopher John Young, Benjamin James Lawry, Abra E. Ziegler, Hunter Anne Knox, Aleksandra Faust, Timothy J. Draelos, Kristin E. Phillips‐Alonge, Eric P. Chael, Matthew Peterson
Publikováno v:
Bulletin of the Seismological Society of America. 108:1346-1354
Autor:
Matthew J. Marinella, James B. Aimone, John H. Naegle, Fredrick Rothganger, Samuel A. Mulder, Nadine E. Miner, Craig M. Vineyard, Kristofor D. Carlson, Steven J. Plimpton, Conrad D. James, Aleksandra Faust, Timothy J. Draelos
Publikováno v:
Biologically Inspired Cognitive Architectures. 19:49-64
Biological neural networks continue to inspire new developments in algorithms and microelectronic hardware to solve challenging data processing and classification problems. Here, we survey the history of neural-inspired and neuromorphic computing in
Autor:
Timothy J. Draelos, Conrad D. James, James B. Aimone, Justin E. Doak, Michael R. Smith, Joe Ingram, Christopher A. Lamb
Publikováno v:
ICMLA
It is needed to ensure the integrity of systems that process sensitive information and control many aspects of everyday life. We examine the use of machine learning algorithms to detect malware using the system calls generated by executables-alleviat
Publikováno v:
Bulletin of the Seismological Society of America. 105:2453-2467
Given a set of observations within a specified time window, a fitness value is calculated at each grid node by summing station‐specific conditional fitness values. Assuming each observation was generated by a refracted P wave, these values are prop
Autor:
Benjamin James Lawry, Eric P. Chael, Christopher John Young, Abra E. Ziegler, Kristin Philips-Alonge, Hunter Anne Knox, Aleksandra Faust, Timothy J. Draelos, Matthew Peterson
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d2a588b5aa73a19f5b62e2bcb393fa01
https://doi.org/10.2172/1596198
https://doi.org/10.2172/1596198
Autor:
Craig M. Vineyard, James B. Aimone, Nadine E. Miner, Jonathan A. Cox, Timothy J. Draelos, Kristofor D. Carlson, Conrad D. James, William Severa, Christopher C. Lamb
Publikováno v:
IJCNN
Neural machine learning methods, such as deep neural networks (DNN), have achieved remarkable success in a number of complex data processing tasks. These methods have arguably had their strongest impact on tasks such as image and audio processing —