In this paper, we review our work on a time series forecasting methodology based on the combination of unsupervised clustering and artificial neural networks. To address noise and...
Nicos G. Pavlidis, Vassilis P. Plagianakos, Dimitr...
Traditional clustering is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. While domain knowledge is always the bes...
This paper proposes a novel approach to discover a set of class specific "composite features" as the feature pool for the detection and classification of complex objects...
Feng Han, Ying Shan, Harpreet S. Sawhney, Rakesh K...
—Temporal-Angular channel sounding measurements of an indoor millimeter wave channel (60 GHz) is analyzed to determine whether ray arrivals at the receiver form clusters in the t...
Behnam Neekzad, Kamran Sayrafian-Pour, John S. Bar...
We propose a multilayered semantic social network model that offers different views of common interests underlying a community of people. The applicability of the proposed model to...