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السجلات المعروضة 1 -- 10 من 35
Arrhythmia classification using DWT-coefficient energy ratios
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Conference Paper)
Certain features present in electrocardiogram (ECG) signals are used to detect different heart conditions. Hence, by developing a system to extract these features, useful information related to the heart conditions could ...
Robust detection of acoustic partial discharge signals in noisy environments
(
Institute of Electrical and Electronics Engineers Inc.
, 2017 , Conference Paper)
Partial discharge (PD) can be used to predict insulation failures in power transformers. Accurate detection of particular PD types has a significant role in anticipating forthcoming outages. However, the noise encountered ...
Handcrafted features with convolutional neural networks for detection of tumor cells in histology images
(
IEEE Computer Society
, 2016 , Conference Paper)
Detection of tumor nuclei in cancer histology images requires sophisticated techniques due to the irregular shape, size and chromatin texture of the tumor nuclei. Some very recently proposed methods employ deep convolutional ...
Car Make And Model Detection System
(
Hamad bin Khalifa University Press (HBKU Press)
, 2014 , Conference Paper)
The deployment of highly intelligent and efficient machine vision systems accomplished to achieve new heights in multiple fields of human activity. A successful replacement of manual intervention with their automated systems ...
Design and analysis of an adaptive compressive sensing architecture for epileptic seizure detection
(
IEEE Computer Society
, 2013 , Conference Paper)
Epileptic detection techniques rely heavily on the Electroencephalography (EEG) as a representative signal carrying valuable information pertaining to the current brain state. In this work, we investigate the stability of ...
Iterative per Group Feature Selection for Intrusion Detection
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Network security is an critical subject in any distributed network. Recently, machine learning has proven their efficiency for intrusion detection. By using a comprehensive dataset with multiple attack types, a well-trained ...
EEG feature extraction and selection techniques for epileptic detection: A comparative study
(
IEEE Computer Society
, 2013 , Conference Paper)
Epileptic detection techniques rely heavily on the Electroencephalography (EEG) as representative signal carrying valuable information pertaining to the current brain state. For these techniques to be efficient and reliable, ...
Performance evaluation for compression-accuracy trade-off using compressive sensing for EEG-based epileptic seizure detection in wireless tele-monitoring
(
IEEE
, 2013 , Conference Paper)
Brain is the most important part in the human body controlling muscles and nerves; Electroencephalogram (EEG) signals record brain electric activities. EEG signals capture important information pertinent to different ...
Energy-Aware Distributed Edge ML for mHealth Applications with Strict Latency Requirements
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Edge machine learning (Edge ML) is expected to serve as a key enabler for real-time mobile health (mHealth) applications. However, its reliability is governed by the limited energy and computing resources of user equipment ...
Performance Comparison of classification algorithms for EEG-based remote epileptic seizure detection in Wireless Sensor Networks
(
IEEE Computer Society
, 2014 , Conference Paper)
Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems. Classification is the most important technique for wide-ranging ...