Christopher Kanan, Ph.D.

Affiliations: 
2004-2006 Computer Science University of Southern California, Los Angeles, CA, United States 
 2007-2013 Computer Science and Engineering University of California, San Diego, La Jolla, CA 
 2013-2015 Jet Propulsion Laboratory California Institute of Technology, Pasadena, CA 
 2015- Chester F. Carlson Center for Imaging Science Rochester Institute of Technology, Rochester, NY, United States 
Area:
Computer Vision, Machine Learning, Object recognition, Neuromorphic algorithms, Theoretical neuroscience
Website:
http://chriskanan.com
Google:
"Christopher Kanan"
Mean distance: 14.57 (cluster 29)
 
SNBCP
Cross-listing: Computational Biology Tree

Parents

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Michael A. Arbib grad student 2005-2007 USC
Garrison Cottrell grad student 2007-2013 UCSD
 (In defense of brain-inspired cognitive models.)
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Publications

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Mahmood U, Shrestha R, Bates DDB, et al. (2021) Detecting Spurious Correlations With Sanity Tests for Artificial Intelligence Guided Radiology Systems. Frontiers in Digital Health. 3: 671015
Hayes TL, Krishnan GP, Bazhenov M, et al. (2021) Replay in Deep Learning: Current Approaches and Missing Biological Elements. Neural Computation. 1-44
da Silva LM, Pereira EM, Salles PG, et al. (2021) Independent real-world application of a clinical-grade automated prostate cancer detection system. The Journal of Pathology
Roady R, Hayes TL, Kemker R, et al. (2020) Are open set classification methods effective on large-scale datasets? Plos One. 15: e0238302
Kafle K, Shrestha R, Kanan C. (2019) Challenges and Prospects in Vision and Language Research. Frontiers in Artificial Intelligence. 2: 28
Parisi GI, Kemker R, Part JL, et al. (2019) Continual lifelong learning with neural networks: A review. Neural Networks : the Official Journal of the International Neural Network Society. 113: 54-71
Kafle K, Shrestha R, Kanan C. (2019) Challenges and Prospects in Vision and Language Research Frontiers in Artificial Intelligence. 2
Acharya M, Kafle K, Kanan C. (2019) TallyQA: Answering Complex Counting Questions Proceedings of the Aaai Conference On Artificial Intelligence. 33: 8076-8084
Kemker R, Salvaggio C, Kanan C. (2018) Algorithms for semantic segmentation of multispectral remote sensing imagery using deep learning Isprs Journal of Photogrammetry and Remote Sensing. 145: 60-77
Kleynhans T, Montanaro M, Gerace A, et al. (2017) Estimating top-of-atmosphere thermal infrared radiance using MERRA-2 atmospheric data Proceedings of Spie. 10178
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