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Now showing items 31-40 of 46
Automatic handedness detection from off-line handwriting
(
IEEE
, 2013 , Conference Paper)
In forensics, the handedness detection or the classification of writers into left or right-handed helps investigators focusing more on a certain category of suspects. However, only a few studies have been carried out in ...
On the use of time-frequency features for detecting and classifying epileptic seizure activities in non-stationary EEG signals
(
Institute of Electrical and Electronics Engineers Inc.
, 2014 , Conference Paper)
This paper proposes new time-frequency features for detecting and classifying epileptic seizure activities in non-stationary EEG signals. These features are obtained by translating and combining the most relevant time-domain ...
Time-frequency image descriptors-based features for EEG epileptic seizure activities detection and classification
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
This paper presents new class of time-frequency (T-F) features for automatic detection and classification of epileptic seizure activities in EEG signals. Most previous methods were based only on signal features derived ...
Automatic prediction of age, gender, and nationality in offline handwriting
(
Hindawi Publishing Corporation
, 2014 , Article)
The classification of handwriting into different categories, such as age, gender, and nationality, has several applications. In forensics, handwriting classification helps investigators focus on a certain category of ...
An online signature verification system for forgery and disguise detection
(
Springer
, 2012 , Conference Paper)
Online signatures are acquired using a digital tablet which provides all the trajectory of the signature as well as the variation in pressure with respect to time. Therefore, online signature verification achieves higher ...
Calibration of time features and frequency features in the time-frequency domain for improved detection and classification of seizure in newborn EEG signals
(
IEEE Computer Society
, 2012 , Conference Paper)
This paper presents new time-frequency features for seizure detection in newborn EEG signals. These features are obtained by calibrating relevant time features and frequency features in the joint time-frequency domain. The ...
Time-frequency features for pattern recognition using high-resolution TFDs: A tutorial review
(
Elsevier Inc.
, 2015 , Article)
This paper presents a tutorial review of recent advances in the field of time-frequency (t, f) signal processing with focus on exploiting (t, f) image feature information using pattern recognition techniques for detection ...
On the selection of time-frequency features for improving the detection and classification of newborn EEG seizure signals and other abnormalities
(2012 , Conference Paper)
This paper presents new time-frequency features for seizure detection in newborn EEG signals. These features are obtained by translating some relevant time features or frequency features to the joint time-frequency domain. ...
Automatic signal abnormality detection using time-frequency features and machine learning: A newborn EEG seizure case study
(
Elsevier B.V.
, 2016 , Article)
Time-frequency (TF) based machine learning methodologies can improve the design of classification systems for non-stationary signals. Using selected TF distributions (TFDs), TF feature extraction is performed on multi-channel ...
High-resolution time-frequency distributions for fall detection
(
SPIE
, 2015 , Conference Paper)
In this paper, we examine the role of high-resolution time-frequency distributions (TFDs) of radar micro-Doppler signatures for fall detection. The work supports the recent and rising interest in using emerging radar ...