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Competitive Quantization for Approximate Nearest Neighbor Search
(
IEEE Computer Society
, 2016 , Article)
In this study, we propose a novel vector quantization algorithm for Approximate Nearest Neighbor (ANN) search, based on a joint competitive learning strategy and hence called as competitive quantization (CompQ). CompQ is ...
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 ...
OSEGNET: OPERATIONAL SEGMENTATION NETWORK FOR COVID-19 DETECTION USING CHEST X-RAY IMAGES
(
IEEE
, 2022 , Conference Paper)
Coronavirus disease 2019 (COVID-19) has been diagnosed automatically using Machine Learning algorithms over chest X-ray (CXR) images. However, most of the earlier studies used Deep Learning models over scarce datasets ...
RELIABLE COVID-19 DETECTION USING CHEST X-RAY IMAGES
(
IEEE Computer Society
, 2021 , Conference Paper)
Coronavirus disease 2019 (COVID-19) has emerged the need for computer-aided diagnosis with automatic, accurate, and fast algorithms. Recent studies have applied Machine Learning algorithms for COVID-19 diagnosis over chest ...
Blind ECG Restoration by Operational Cycle-GANs
(
IEEE Computer Society
, 2022 , Article)
Objective: ECG recordings often suffer from a set of artifacts with varying types, severities, and durations, and this makes an accurate diagnosis by machines or medical doctors difficult and unreliable. Numerous studies ...
Biosignal time-series analysis
(
Elsevier
, 2022 , Book chapter)
In this chapter, recent state-of-the-art techniques in biosignal time-series analysis will be presented. We shall start with the problem of patient-specific ECG beat classification where the objective is to discriminate ...
Robust Peak Detection for Holter ECGs by Self-Organized Operational Neural Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Although numerous R-peak detectors have been proposed in the literature, their robustness and performance levels may significantly deteriorate in low-quality and noisy signals acquired from mobile electrocardiogram (ECG) ...
COVID-19 infection map generation and detection from chest X-ray images
(
Springer Science and Business Media Deutschland GmbH
, 2021 , Article)
Computer-aided diagnosis has become a necessity for accurate and immediate coronavirus disease 2019 (COVID-19) detection to aid treatment and prevent the spread of the virus. Numerous studies have proposed to use Deep ...
SRL-SOA: SELF-REPRESENTATION LEARNING WITH SPARSE 1D-OPERATIONAL AUTOENCODER FOR HYPERSPECTRAL IMAGE BAND SELECTION
(
IEEE Computer Society
, 2022 , Conference Paper)
The band selection in the hyperspectral image (HSI) data processing is an important task considering its effect on the computational complexity and accuracy. In this work, we propose a novel framework for the band selection ...