Object Detection Professors in Global

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Ekta Vats
Uppsala University Sweden
computer vision
optical character recognition
machine learning
image analysis
human action recognition
deep learning
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Sankaran Iyer
University of New South Wales Australia
object detection
pedestrian detection
anomaly detection
computer vision
deep learning
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Maria Amer
Concordia University Canada
object detection
object tracking
computer vision
activity recognition
deep learning
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Du Huynh
University of Western Australia Australia
object detection
computer vision
pattern recognition
machine learning
visual tracking
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Allison Sekuler
McMaster University Canada
object recognition
face recognition
motion perception
visual perception
perceptual learning
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Leman Akoglu
Carnegie Mellon University United States of America
anomaly detection
outlier detection
fraud detection
machine learning
pattern discovery
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Olga Veksler
University of Waterloo Canada
salient object detection
computer vision
machine learning
image segmentation
deep learning
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Marios Savvides
Carnegie Mellon University United States of America
object detection
face detection
face recognition
machine learning
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Roberto Cipolla
University of Cambridge United Kingdom
object detection
computer vision
face recognition
gesture recognition
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Doris Tsao
University of California, Berkeley United States of America
object recognition
object segmentation
visual object representation
visual tracking
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Julian Kooij
Delft University of Technology Netherlands
3d object detection
computer vision
visual localization
deep learning
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Changming Sun
University of New South Wales Australia
feature detection
computer vision
image matching
deep learning
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Josien Pluim
Eindhoven University of Technology Belgium
image detection
machine learning
image segmentation
deep learning
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Rakesh Mishra
University of New Brunswick Canada
ai-based object detection
computer vision
machine learning
deep learning
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Atsuto Maki
KTH Royal Institute of Technology Sweden
motion object recognition
computer vision
machine learning
deep learning
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Computer Vision
RWTH Aachen University Germany
visual object recognition
computer vision
machine learning
self-localization
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Ke Chen
University of Manchester United Kingdom
computer vision
pattern recognition
machine perception
machine learning
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Hermann Ney
RWTH Aachen University Germany
image object recognition
machine learning
sign language recognition
text image recognition
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Mohammed Bennamoun
University of Western Australia Australia
3d object recognition
computer vision
machine learning
deep learning
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Len Hamey
Macquarie University Australia
computer vision
pattern recognition
machine learning
image analysis
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Pietro Perona
California Institute of Technology United States of America
visual recognition
machine vision
machine learning
visual categorization
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