This paper's intention is to adapt prediction algorithms well known in the field of time series analysis to problems being faced in the field of mobile robotics and Human-Robo...
In this paper we present a comparison of multiple cluster algorithms and their suitability for clustering text data. The clustering is based on similarities only, employing the Kol...
Tina Geweniger, Frank-Michael Schleif, Alexander H...
Abstract. We previously proposed a neural segmentation model suitable for implementation with complementary metal-oxide-semiconductor (CMOS) circuits. The model consists of neural ...
Gessyca Maria Tovar, Tetsuya Asai, Yoshihito Amemi...
Asbestos-related illnesses become a nationwide problem in Japan. Now human inspectors check whether asbestos is contained in building material or not. To judge whether the specimen...
Abstract. Feature selection has improved the performance of text clustering. Global feature selection tries to identify a single subset of features which are relevant to all cluste...
Marcelo N. Ribeiro, Manoel J. R. Neto, Ricardo Bas...
Abstract. The concept of Ensemble Learning has been shown to increase predictive power over single base learners. Given the bias-variancecovariance decomposition, diversity is char...
Several applications would emerge from the development of efficient and robust sound classification systems able to identify the nature of non-speech sound sources. This paper prop...
Mauricio Kugler, Victor Alberto Parcianello Benso,...
We present a system for regression using MLP neural networks with hyperbolic tangent functions in the input, hidden and output layer. The activation functions in the input and outp...