Remote Detection Professors in Global

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Guofei Gu
Texas A&M University United States of America
intrusion detection
anomaly detection
botnet detection
advanced persistent threat detection
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Kavita Bala
Cornell University Netherlands
material recognition
computer vision
visual search detection
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Ke Chen
University of Manchester United Kingdom
pattern recognition
machine perception
computer vision
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Kristen Grauman
University of Texas at Austin United States of America
visual recognition
object activity recognition
machine perception
computer vision
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Medhat Moussa
University of Guelph Canada
pattern recognition
computer vision
robot learning
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Raquel Urtasun
University of Toronto Canada
ai remote sensing
computer vision
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Marios Savvides
Carnegie Mellon University United States of America
object detection
face detection
face recognition
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Marios Savvides
Carnegie Mellon University United States of America
object detection
face detection
face recognition
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Yunzhong Hou
Australian National University Australia
multi-view detection
computer vision
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Sandro Etalle
Eindhoven University of Technology Belgium
intrusion detection
network monitoring
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Peter Stiller
Texas A&M University United States of America
image recognition
computer vision
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Rakesh Mishra
University of New Brunswick Canada
ai-based object detection
computer vision
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Kostas Daniilidis
University of Pennsylvania United States of America
robotic perception
computer vision
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Kin-choong Yow
University of Regina Canada
pattern recognition
computer vision
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Rama Chellappa
Johns Hopkins University United States of America
pattern recognition
computer vision
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Ram Nevatia
University of Southern California United States of America
pattern recognition
computer vision
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Majid Mirmehdi
University of Bristol United Kingdom
pattern recognition
computer vision
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Ram Nevatia
University of Southern California United States of America
pattern recognition
computer vision
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John Daugman
University of Cambridge United Kingdom
pattern recognition
computer vision
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Christian Rupprecht
University of Oxford United Kingdom
pattern recognition
computer vision
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Michael Bronstein
Imperial College London United Kingdom
pattern recognition
computer vision
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