John Canny is affiliated with the University of California, Berkeley in the United States. Their research spans primarily the field of Computer Science, with a focus on several subfields including Computer Vision and Pattern Recognition, Artificial Intelligence, Human-Computer Interaction, Surgery, and Molecular Biology.
The main topics covered in their work include:
John Canny has contributed to a range of recent publications, with sample papers including:
Their frequent co-authors include:
John Canny has published extensively in venues such as:
In addition to journal and conference publications, John Canny has authored a book titled Artificial Intelligence for Human Computer Interaction: A Modern Approach, published in 2021 by Springer Nature.
John Canny's contributions have been recognized with the award of ACM Fellow in 2020, for work spanning robotics, machine perception, human-computer interaction, and ubiquitous computing.
John Canny
John F. Canny
John Canny
J. Canny
John Canny
John Canny;John Reif
M.C. Lin;J.F. Canny
John Canny
Roshan Rao;Nicholas Bhattacharya;Neil Thomas;Yan Duan
Bruce Donald;Patrick Xavier;John Canny;John Reif
Brian Mirtich;John Canny
John Canny
Z. Li;J. Canny
D. Manocha;J.F. Canny
Ming Chieh Lin;John F. Canny
Jinkyu Kim;John Canny
Roshan Rao;Nicholas Bhattacharya;Neil Thomas;Yan Duan
Z. Gigus;J. Canny;R. Seidel
Roshan Rao;Jason Liu;Robert Verkuil;Joshua Meier
John F. Canny;Ming C. Lin
P. Jacobs;J. Canny
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