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» Facial Expression Recognition Using a Neural Network
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NN
1997
Springer
174views Neural Networks» more  NN 1997»
15 years 3 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani

Book
996views
16 years 9 months ago
The Scientist and Engineer's Guide to Digital Signal Processing
"The world of science and engineering is filled with signals: images from remote space probes, voltages generated by the heart and brain, radar and sonar echoes, seismic vibra...
Steve Smith
IJCNN
2000
IEEE
15 years 3 months ago
Competing Hidden Markov Models on the Self-Organizing Map
This paper presents an unsupervised segmentation method for feature sequences based on competitivelearning hidden Markov models. Models associated with the nodes of the Self-Organ...
Panu Somervuo
ICANN
2005
Springer
15 years 5 months ago
Fast Color-Based Object Recognition Independent of Position and Orientation
Small mobile robots typically have little on-board processing power for time-consuming vision algorithms. Here we show how they can quickly extract very dense yet highly useful inf...
Martijn van de Giessen, Jürgen Schmidhuber
CORR
2006
Springer
111views Education» more  CORR 2006»
14 years 11 months ago
An associative memory for the on-line recognition and prediction of temporal sequences
This paper presents the design of an associative memory with feedback that is capable of on-line temporal sequence learning. A framework for on-line sequence learning has been prop...
Joy Bose, Stephen B. Furber, Jonathan L. Shapiro