Browsing by Subject "image segmentation"
Now showing items 1-6 of 6
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Adversarial Attacks for Image Segmentation on Multiple Lightweight Models
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)Due to the powerful ability of data fitting, deep neural networks have been applied in a wide range of applications in many key areas. However, in recent years, it was found that some adversarial samples easily fool the ... -
COVID-19 infection localization and severity grading from chest X-ray images
( Elsevier Ltd , 2021 , Article)The immense spread of coronavirus disease 2019 (COVID-19) has left healthcare systems incapable to diagnose and test patients at the required rate. Given the effects of COVID-19 on pulmonary tissues, chest radiographic ... -
Detection and severity classification of COVID-19 in CT images using deep learning
( MDPI , 2021 , Article)Detecting COVID-19 at an early stage is essential to reduce the mortality risk of the patients. In this study, a cascaded system is proposed to segment the lung, detect, localize, and quantify COVID-19 infections from ... -
Effectiveness of combined time-frequency imageand signal-based features for improving the detection and classification of epileptic seizure activities in EEG signals
( IEEE , 2014 , Conference Paper)This paper presents new time-frequency (T-F) features to improve the detection and classification of epileptic seizure activities in EEG signals. Most previous methods were based only on signal features derived from the ... -
A methodology for time-frequency image processing applied to the classification of nonstationary multichannel signals using instantaneous frequency descriptors with application to newborn EEG signals
( Springer , 2003 , Article)This article presents a general methodology for processing non-stationary signals for the purpose of classification and localization. The methodology combines methods adapted from three complementary areas: time-frequency ... -
Ultrasound Intima-Media Complex (IMC) Segmentation Using Deep Learning Models
( Multidisciplinary Digital Publishing Institute (MDPI) , 2023 , Article)Common carotid intima-media thickness (CIMT) is a common measure of atherosclerosis, often assessed through carotid ultrasound images. However, the use of deep learning methods for medical image analysis, segmentation and ...