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Guest Editorial

Freeman, William and Perona, Pietro and Schölkopf, Bernhard (2008) Guest Editorial. International Journal of Computer Vision, 77 (1-3). p. 1. ISSN 0920-5691. https://resolver.caltech.edu/CaltechAUTHORS:20140730-101716153

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Abstract

Computational Vision and Machine Learning have become synergistic fields of research. Modern machine learning techniques have improved the state of the art in computer vision and catalized re-thinking of key problems, such as recognition and tracking. In turn, vision has broadened the scope of machine learning, offering rich new challenges and highlighting the importance of representations.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1007/s11263-008-0127-7DOIArticle
https://rdcu.be/btlLpPublisherFree ReadCube access
ORCID:
AuthorORCID
Freeman, William0000-0003-3559-5270
Perona, Pietro0000-0002-7583-5809
Additional Information:© Springer Science+Business Media, LLC 2008.
Subject Keywords:Pattern Recognition, Image Processing and Computer Vision, Artificial Intelligence (incl. Robotics), Computer Imaging, Vision, Pattern Recognition and Graphics
Issue or Number:1-3
Record Number:CaltechAUTHORS:20140730-101716153
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20140730-101716153
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:47590
Collection:CaltechAUTHORS
Deposited By: Caroline Murphy
Deposited On:25 Aug 2014 21:45
Last Modified:09 Mar 2020 13:18

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