Context-Based Estimation of Class Priors for Improving Performance of Classifiers
Context-Based Estimation of Class Priors for Improving Performance of Classifiers with Large Number of Classes
by Dr. Abhijit Mahalanobis, University of Arizona
December 9, 2022
Webinar sponsored by IEEE GRSS
Modern classifiers can be trained to recognize thousands of classes but are likely to encounter only a subset of these in any given deployment. Unlike humans, most classification strategies do not learn to utilize the context of the deployment (i.e. the likelihood of class occurrence in a given setting) to influence the decision strategy. To address this issue, this webinar describes a method for estimating the prior probabilities for each class based on the observed histogram of the classifiers’ decisions over time.
More details at: https://www.grss-ieee.org/events/cont...
The webinar is hosted by IEEE GRSS Image Analysis and Data Fusion (IADF) Technical Committee. Visit https://www.grss-ieee.org/technical-c... to know more about it.
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