Classifying an event captured in an image is useful for understanding the contents of the image. The captured event provides context to refine models for the presence and appearan...
AdaBoost and support vector machines (SVM) algorithms are commonly used in the field of object recognition. As classifiers, their classification performance is sensitive to affect...
It is labor-intensive to manually verify the outputs of a large set of tests that are not equipped with test oracles. Test selection helps to reduce this cost by selecting a small...
—Our sensor selection algorithm targets the problem of global self-localization of multi-sensor mobile robots. The algorithm builds on the probabilistic reasoning using Bayes fil...
Sreenivas R. Sukumar, Hamparsum Bozdogan, David L....
In this paper we propose a method for selecting an appropriate subset of sensors with a view to minimize estimation error while tracking a target with sensors spread across in a 2...