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Found 5 papers, 1 papers with code
Multi-class versus One-class classifier in spontaneous speech analysis oriented to Alzheimer Disease diagnosis
Most of medical developments require the ability to identify samples that are anomalous with respect to a target group or control group, in the sense they could belong to a new, previously unseen class or are not class data.
Novel EEG-based BCIs for Elderly Rehabilitation Enhancement
The ageing process may lead to cognitive and physical impairments, which may affect elderly everyday life.
Serial-EMD: Fast Empirical Mode Decomposition Method for Multi-dimensional Signals Based on Serialization
Empirical mode decomposition (EMD) has developed into a prominent tool for adaptive, scale-based signal analysis in various fields like robotics, security and biomedical engineering.
Learning from Incomplete Features by Simultaneous Training of Neural Networks and Sparse Coding
A new supervised learning method is developed to train a general classifier, such as a logistic regression or a deep neural network, using only a subset of features per sample, while assuming sparse representations of data vectors on an unknown dictionary.
Supervised learning with incomplete data via sparse representations
This paper addresses the problem of training a classifier on incomplete data and its application to a complete or incomplete test dataset.
