Abstract This work introduces a self-supervised architecture for robust classification of moving obstacles in urban environments. Our approach presents a hierarchical scheme that r...
Roman Katz, Juan Nieto, Eduardo Mario Nebot, Bertr...
In this paper we present a framework for semantic scene parsing and object recognition based on dense depth maps. Five viewindependent 3D features that vary with object class are e...
Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
Textual-case based reasoning (TCBR) systems where the problem and solution are in free text form are hard to evaluate. In the absence of class information, domain experts are neede...
M. A. Raghunandan, Nirmalie Wiratunga, Sutanu Chak...
— We present a hybrid data mining approach to detect malicious executables. In this approach we identify important features of the malicious and benign executables. These feature...
Mohammad M. Masud, Latifur Khan, Bhavani M. Thurai...