In this paper we present a novel framework for evolving ART-based classification models, which we refer to as MOME-ART. The new training framework aims to evolve populations of ART...
Rong Li, Timothy R. Mersch, Oriana X. Wen, Assem K...
This research presents a classifier that aims to provide insight into a dataset in addition to achieving classification accuracies comparable to other algorithms. The classifier c...
Producing consistent segmentations of lung nodules in CT scans is a persistent problem of image processing algorithms. Many hard-segmentation approaches are proposed in the literat...
Olga Zinoveva, Dmitry Zinovev, Stephen A. Siena, D...
Background: Biomedical ontologies are critical for integration of data from diverse sources and for use by knowledge-based biomedical applications, especially natural language pro...
We describe a realtime system for finding and tracking unstructured paths in off-road conditions. The system was designed as part of the recent Darpa Grand Challenge and was teste...