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Heart sound anomaly and quality detection using ensemble of neural networks without segmentation
(
IEEE Computer Society
, 2016 , Conference Paper)
Phonocardiogram (PCG) signal is used as a diagnostic test in ambulatory monitoring in order to evaluate the heart hemodynamic status and to detect a cardiovascular disease. The objective of this study is to develop an ...
Outlier edge detection using random graph generation models and applications
(
Springer
, 2017 , Article)
Outliers are samples that are generated by different mechanisms from other normal data samples. Graphs, in particular social network graphs, may contain nodes and edges that are made by scammers, malicious programs or ...
Comparison of polarimetric SAR features for terrain classification using incremental training
(
Electromagnetics Academy
, 2017 , Conference Paper)
In this study, the most commonly used polarimetric SAR features including the complete coherency (or covariance) matrix information, features obtained from several coherent and incoherent target decompositions, the ...
1-D Convolutional Neural Networks for Signal Processing Applications
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Conference Paper)
1D Convolutional Neural Networks (CNNs) have recently become the state-of-the-art technique for crucial signal processing applications such as patient-specific ECG classification, structural health monitoring, anomaly ...
The effect of automated taxa identification errors on biological indices
(
Elsevier Ltd
, 2017 , Article)
In benthic macroinvertebrate biomonitoring systems, the target is to determine the status of ecosystems based on several biological indices. To increase cost-efficiency, computer-based taxa identification for image data ...
Convolutional Neural Networks for patient-specific ECG classification
(
IEEE
, 2015 , Conference Paper)
We propose a fast and accurate patient-specific electrocardiogram (ECG) classification and monitoring system using an adaptive implementation of 1D Convolutional Neural Networks (CNNs) that can fuse feature extraction and ...
Learning to rank salient segments extracted by multispectral Quantum Cuts
(
Elsevier B.V.
, 2016 , Article)
and third, multispectral approach is followed to generate multiple proposals instead of a single proposal as in Quantum Cuts. The proposed learn-to-rank algorithm is then applied to these multiple proposals in order to ...
Optimization of linear zigzag insert metastructures for low-frequency vibration attenuation using genetic algorithms
(
Academic Press
, 2017 , Article)
Vibration suppression remains a crucial issue in the design of structures and machines. Recent studies have shown that with the use of metamaterial inspired structures (or metastructures), considerable vibration attenuation ...
Salient object segmentation based on linearly combined affinity graphs
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Conference Paper)
In this paper, we propose a graph affinity learning method for a recently proposed graph-based salient object detection method, namely Extended Quantum Cuts (EQCut). We exploit the fact that the output of EQCut is ...
Wireless and real-time structural damage detection: A novel decentralized method for wireless sensor networks
(
Elsevier
, 2018 , Article)
© 2018 Elsevier Ltd Being an alternative to conventional wired sensors, wireless sensor networks (WSNs) are extensively used in Structural Health Monitoring (SHM) applications. Most of the Structural Damage Detection (SDD) ...