Automatic sound recognition (ASR) has attracted increased and wide ranging interests in
recent years. In this paper, we carry out a review of some important contributions in ASR …

This study compares several methods for creating a multiclass, support vector machines-
based (SVM) classifier from a set of binary SVM classifiers. This research aims to identify …

Randomized decision trees and forests have a rich history in machine learning and have
seen considerable success in application, perhaps particularly so for computer vision …

We present a new method, filter tree, for reducing k-class classification to binary
classification. The filter tree is provably consistent in the sense that given an optimal binary …

This paper builds on the technique of feature extraction from the spectrogram image of
sound signals for automatic sound recognition. The spectrogram image is divided into …

Subgroup discovery aims at finding subsets of a population whose class distribution is
significantly different from the overall distribution. It has previously predominantly been …

In this paper, we are interested in making decisions by combining classifiers providing
uncertain outputs, in the form of sets of probability distributions. More precisely, each …

Prediction of unknown fault of induction motor is an important task to prevent it from
unscheduled shutdown. Here, an unknown fault of induction motor has been classified and …

When people observe the actions of others, they naturally try to understand the underlying
intentions. This behavior is called action understanding, and it has an important influence on …

In this paper, we compare the performance of classification techniques for multiclass support
vector machines in an unstructured environment. In particular, we consider the following …