We propose a novel approach to face identification and verification based on the Error Correcting Output Coding (ECOC) classifier design concept. In the training phase the client s...
Josef Kittler, Reza Ghaderi, Terry Windeatt, Jiri ...
—This article proposes a general extension of the Error Correcting Output Codes (ECOC) framework to the online learning scenario. As a result, the final classifier handles the ...
Sergio Escalera, David Masip, Eloi Puertas, Petia ...
This paper explores in detail the use of Error Correcting Output Coding (ECOC) for learning text classifiers. We show that the accuracy of a Naive Bayes Classifier over text class...
Error correcting output codes (ECOC) represent a classification technique that allows a successful extension of binary classifiers to address the multiclass problem. In this paper...
For purpose of object recognition, we learn one discriminative classifier based on one prototype, using shape context distances as the feature vector. From multiple prototypes, th...
The Error Correcting Output Coding (ECOC) approach to classifier design decomposes a multi-class problem into a set of complementary two-class problems. We show how to apply the E...
Josef Kittler, Reza Ghaderi, Terry Windeatt, Jiri ...