The objective of this paper is to illustrate the application of genetic programming to evolve classifiers for multi-channel time series data. The paper shows how high performance d...
Abstract-- Automatic recognition of activities using time series data collected from exercise can facilitate development of applications that motivate people to exercise more frequ...
Pekka Siirtola, Perttu Laurinen, Eija Haapalainen,...
Segmentation of CSF and pulsative blood flow, based on a single phase contrast MRA (PC-MRA) image can lead to imperfect classifications. In this paper, we present a novel automated...
Ali Gooya, Hongen Liao, Kiyoshi Matsumiya, Ken Mas...
Similarity search is an important problem in information retrieval. This similarity is based on a distance. Symbolic representation of time series has attracted many researchers re...
Muhammad Marwan Muhammad Fuad, Pierre-Francois Mar...
: A new supervised learning procedure for training RBF networks is proposed. It uses a pair of parallel running Kalman filters to sequentially update both the output weights and th...