The required amount of labeled training data for object detection and classification is a major drawback of current methods. Combining labeled and unlabeled data via semisupervise...
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
In a multiple classifier system, dynamic selection (DS) has been used successfully to choose only the best subset of classifiers to recognize the test samples. Dos Santos et al...
Paulo Rodrigo Cavalin, Robert Sabourin, Ching Y. S...
Background: The advent of the technology of DNA microarrays constitutes an epochal change in the classification and discovery of different types of cancer because the information ...
We address the problem of learning classifiers for several related tasks that may differ in their joint distribution of input and output variables. For each task, small