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Now showing items 21-30 of 31
Recognition of off-line handwritten Arabic words using neural network
(
IEEE
, 2006 , Conference Paper)
Neural network (NN) have been used with some success in recognizing printed Arabic words. In this paper, a complete scheme for unconstrained Arabic handwritten word recognition based on a Neural network is proposed and ...
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 ...
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 ...
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 ...
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. ...
Computer aided diagnosis system based on machine learning techniques for lung cancer
(2012 , Conference Paper)
Cancer is a leading cause of death worldwide. Lung cancer is a type of cancer that is considered as one of the most leading causes of death globally. In Malaysia, it is the 3rd common cancer type and the 2nd type of cancer ...
On the applicability of 2D local binary patterns for identifying electrical appliances in non-intrusive load monitoring
(
Springer
, 2021 , Conference Paper)
In recent years, the automatic identification of electrical devices through their power consumption signals finds a variety of applications in smart home monitoring and non-intrusive load monitoring (NILM). This work ...
Efficient multi-descriptor fusion for non-intrusive appliance recognition
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Consciousness about power consumption at the appliance level can assist user in promoting energy efficiency in households. In this paper, a superior non-intrusive appliance recognition method that can provide particular ...
Improving In-Home Appliance Identification Using Fuzzy-Neighbors-Preserving Analysis Based QR-Decomposition
(
Springer Science and Business Media Deutschland GmbH
, 2021 , Conference Paper)
This paper proposes a new appliance identification scheme by introducing a novel approach for extracting highly discriminative characteristic sets that can considerably distinguish between various appliance footprints. In ...