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Long-term epileptic EEG classification via 2D mapping and textural features
(
Elsevier Ltd
, 2015 , Article)
Interpretation of long-term Electroencephalography (EEG) records is a tiresome task for clinicians. This paper presents an efficient, low cost and novel approach for patient-specific classification of long-term epileptic ...
ShakeMe: Key generation from shared motion
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
Devices equipped with accelerometer sensors such as today's mobile devices can make use of motion to exchange information. A typical example for shared motion is shaking of two devices which are held together in one hand. ...
Unsupervised feature selection method for improved human gait recognition
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
Gait recognition is an emerging biometric technology which aims to identify people purely through the analysis of the way they walk. The technology has attracted interest as a method of identification because it is ...
Combining Fisher locality preserving projections and passband DCT for efficient palmprint recognition
(
Elsevier B.V.
, 2015 , Article)
In this paper a new graph based approach referred to as Fisher Locality Preserving Projections (FLPP) is proposed for efficient palmprint recognition. The technique employs two graphs with the first being used to characterize ...
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 ...
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 ...
Principles of time-frequency feature extraction for change detection in non-stationary signals: Applications to newborn EEG abnormality detection
(
Elsevier Ltd
, 2015 , Article)
This paper considers the general problem of detecting change in non-stationary signals using features observed in the time-frequency (t,f) domain, obtained using a class of quadratic time-frequency distributions (QTFDs). ...