Explosives Detection Professors in Global

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Sankaran Iyer
University of New South Wales Australia
object detection
pedestrian detection
anomaly detection
surveillance security
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Guofei Gu
Texas A&M University United States of America
intrusion detection
anomaly detection
advanced persistent threat detection
botnet detection
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Leman Akoglu
Carnegie Mellon University United States of America
anomaly detection
fraud detection
outlier detection
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Daniel Prober
Yale University United States of America
x-ray detectors
uv detectors
microwave detectors
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Tengyao Wang
London School of Economics United Kingdom
sparse signal detection
change-point detection
statistical learning-assisted material discovery
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Duncan Chalmers
University of New South Wales Australia
explosives
detection analysis
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Andrea Martin
University of Southern California United States of America
chemical detection
biological detection
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Gianluca Piazza
Carnegie Mellon University United States of America
chemical detection
biological detection
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Mehrdad Saif
University of Windsor Canada
attack detection
fault detection
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Erza Aminanto
Monash University Australia
intrusion detection
anomaly detection
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Marios Savvides
Carnegie Mellon University United States of America
object detection
face detection
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Francisca Munoz Sanchez
University of Manchester United Kingdom
radiation detection
silicon detectors
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Pierre Tardif
University of Sherbrooke Canada
intrusion detection
anomaly detection
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Liam Marsh
University of Manchester United Kingdom
metal detection
landmine erw detection
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J.c. Van Gemert
Delft University of Technology Netherlands
detection
pattern recognition
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S.m.parvez Mahbub
University of New South Wales Australia
rapid screening of explosives
environmental hazard monitoring
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Simon Viel
Carleton University Canada
dark matter detection
detector simulation
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Maria Amer
Concordia University Canada
object detection
object tracking
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Du Huynh
University of Western Australia Australia
object detection
pattern recognition
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Paula Branco
University of Ottawa Canada
anomaly detection
fraud detection
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Christian Maack
Aalborg University Denmark
anomaly detection
fault detection
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