Dimensionality reduction is an important preprocessing step in high-dimensional data analysis without losing intrinsic information. The problem of semi-supervised nonlinear dimensi...
Data mining tasks results are usually improved by reducing the dimensionality of data. This improvement however is achieved harder in the case that data lay on a non linear manifol...
This paper addresses the topic of how architectural visual experience can be represented and utilised by a software system. The long-term aim is to equip an artificial agent with ...
Stephan K. Chalup, Riley Clement, Chris Tucker, Mi...
In this paper we present a novel method for reducing false positives in breast mass detection. Our approach is based on using the Two-Dimensional Principal Component Analysis (2DPC...
Abstract— Although the human hand is a complex biomechanical system, only a small set of features may be necessary for observation learning of functional grasp classes. We explor...
Lillian Y. Chang, Nancy S. Pollard, Tom M. Mitchel...