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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 
 2015-2022 Chester F. Carlson Center for Imaging Science Rochester Institute of Technology, Rochester, NY, United States 
 2022- Computer Science University of Rochester, Rochester, NY 
Area:
Deep Learning, Artificial Intelligence, Computer Vision, Cognitive Science
Website:
http://chriskanan.com
Google:
"Christopher Kanan"
Mean distance: 14.57 (cluster 29)
 
SNBCP
Cross-listing: Computational Biology Tree

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Publications

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Raciti P, Sue J, Retamero JA, et al. (2022) Clinical Validation of Artificial Intelligence-Augmented Pathology Diagnosis Demonstrates Significant Gains in Diagnostic Accuracy in Prostate Cancer Detection. Archives of Pathology & Laboratory Medicine
Mahmood U, Bates DDB, Erdi YE, et al. (2022) Deep Learning and Domain-Specific Knowledge to Segment the Liver from Synthetic Dual Energy CT Iodine Scans. Diagnostics (Basel, Switzerland). 12
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
Mahmood U, Apte A, Kanan C, et al. (2021) Quality control of radiomic features using 3D-printed CT phantoms. Journal of Medical Imaging (Bellingham, Wash.). 8: 033505
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
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