In this paper, we propose a novel supervised hierarchical sparse coding model based on local image descriptors for classification tasks. The supervised dictionary training is perf...
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
This paper describes a two-stage system for the recognition ge meter values. A feed-forward Neural Abstraction Pyramid is initialized in an unsupervised manner and trained in a sup...
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
This paper presents an improved technique to detect evoked potentials in continuous EEG recordings using a spiking neural network. Human EEG signals recorded during spell checking,...
Piyush Goel, Honghai Liu, David J. Brown, Avijit D...