Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Ensemble of Transfer, Semi-supervised and Supervised Learning Methods
  for Pathological Heart Sound Classification   In this work, we propose an ensemble of classifiers to distinguish between
various degrees of abnormalities of the heart using Phonocardiogram (PCG)
signals acquired using digital stethoscopes in a clinical setting, for the
INTERSPEECH 2018 Computational Paralinguistics (ComParE) Heart Beats
SubChallenge. Our primary classification framework constitutes a convolutional
neural network with 1D-CNN time-convolution (tConv) layers, which uses features
transferred from a model trained on the 2016 Physionet Heart Sound Database. We
also employ a Representation Learning (RL) approach to generate features in an
unsupervised manner using Deep Recurrent Autoencoders and use Support Vector
Machine (SVM) and Linear Discriminant Analysis (LDA) classifiers. Finally, we
utilize an SVM classifier on a high-dimensional segment-level feature extracted
using various functionals on short-term acoustic features, i.e., Low-Level
Descriptors (LLD). An ensemble of the three different approaches provides a
relative improvement of 11.13% compared to our best single sub-system in terms
of the Unweighted Average Recall (UAR) performance metric on the evaluation
dataset.

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The categories of this paper are: hep-ph
6
The categories of this paper are: astro-ph
27
The categories of this paper are: comp-gas
14
The categories of this paper are: math-ph
5
The categories of this paper are: gr-qc
30
The categories of this paper are: q-alg
31
The categories of this paper are: ao-sci
16
The categories of this paper are: stat
22
The categories of this paper are: chao-dyn
32
The categories of this paper are: atom-ph
3
The categories of this paper are: physics
17
The categories of this paper are: q-fin
33
The categories of this paper are: plasm-ph
19
The categories of this paper are: eess
29
The categories of this paper are: funct-an
8
The categories of this paper are: hep-ex