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Review of Computational Techniques for the Analysis of Abnormal Patterns of ECG Signal Provoked by Cardiac Disease

Computer Modeling in Engineering & Sciences 2021年第9期127卷 875-906页

作者： Revathi Jothiramalingam Anitha jude duraisamy jude hemanth Kalaignarkarunanidhi Institute of Technology Coimbatore641402India Department of ECE Karunya Institute of Technology and SciencesCoimbatore641114India

The 12-lead ECG aids in the diagnosis of myocardial infarction and is helpful in the prediction of cardiovascular disease *** does,though,have certain *** other electrocardiographic anomalies such as Left Bundle Branch Block and Left Ventricular Hypertrophy syndrome,the ECG signal withMyocardial Infarction is difficult to *** diseases cause variations in the ST portion of the ECG *** reduces the clarity of ECG signals,making itmore difficult to diagnose these *** a result,the specialist is misled into making an erroneous diagnosis by using the incorrect therapeutic *** on these concepts,this article reviews the different procedures involved in ECG signal pre-processing,feature extraction,feature selection,and classification techniques to diagnose heart disorders such as LeftVentricularHypertrophy,Bundle Branch Block,andMyocardial *** reveals the flaws and benefits in each segment,as well as recommendations for developing more advanced and robustmethods for diagnosing these diseases,which will increase the system’s *** current issues and prospective research directions are also addressed.

关键词： Bundle branch block myocardial infarction left ventricular hypertrophy feature selection feature extraction classification

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Deep Feature Extraction and Feature Fusion for Bi-Temporal Satellite Image Classification

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Computers, Materials & Continua 2021年第1期66卷 373-388页

作者： Anju Asokan Bogdan Patrut Dana Danciulescu D.jude hemanth Department of ECE Karunya Institute of Technology and SciencesCoimbatoreIndia Department of Computer Science Alexandru Ioan Cuza University of la?ila?iRomania Department of Computer Science University of CraiovoCraiovoRomania

Multispectral images contain a large amount of spatial and spectral data which are effective in identifying change *** feature extraction is important for multispectral image classification and is evolving as an interesting research area in change ***,many deep learning framework based approaches do not consider both spatial and textural details into *** order to handle this issue,a Convolutional Neural Network(CNN)based multi-feature extraction and fusion is introduced which considers both spatial and textural *** method uses CNN to extract the spatio-spectral features from individual channels and fuse them with the textural *** the fused image is classified into change and unchanged *** presence of mixed pixels in the bitemporal satellite images affect the classification accuracy due to the misclassification *** proposed method was compared with six state-of-theart change detection methods and *** main highlight of this method is that by taking into account the spatio-spectral and textural information in the input channels,the mixed pixel problem is *** indicate the effectiveness of this method and demonstrate that it possesses low misclassification errors,higher overall accuracy and kappa coefficient.

关键词： Remote sensing convolutional neural network deep learning multispectral bitemporal change detection

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Reversible Data Hiding Based on Varying Radix Numeral System

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Computers, Materials & Continua 2021年第10期69卷 283-300页

作者： J.Hemalatha S.Geetha R.Geetha C.Balasubramanian Daniela Elena Popescu D.jude hemanth AAA College of Engineering and Technology SivakasiIndia SCOPE VIT UniversityChennaiIndia SENSE VIT UniversityChennaiIndia Department of CSE Kalasalingam Academy of Research and EducationIndia Faculty of Electrical Engineering and Information Technology University of OradeaOradeaRomania Department of ECE Karunya Institute of Technology and SciencesCoimbatoreIndia

A novel image reversible data-hiding scheme based on primitive and varying radix numerical model is presented in this *** varying radix,variable sum of data may be embedded in various pixels of *** scheme is made adaptive using the correlation of the neighboring *** are embedded as blocks of non-uniform length in the high-frequency regions of the rhombus mean interpolated image.A higher amount of data is embedded in the high-frequency regions and lesser data in the low-frequency regions of the *** size of the embedded data depends on the statistics of the pixel distribution in the cover *** of the major issues in reversible data embedding,the location map,is minimized because of the interpolation *** technique,which is actually LSB matching,embeds only the residuals of modulo radix into the LSBs of each *** attacks on this RDH technique will be able to decode the hidden content in the marked *** proposed scheme delivers a prominent visual quality despite high embedding *** tests carried out on over 100 natural image data sets and medical images show an improvement in results compared to the existing *** the algorithm is based on the variable radix number system,it is more resistant to most of the steganographic *** results were compared with a higher embedding capacity of up to 1.5 bpp reversible schemes for parameters like Peak Signal-to-Noise Ratio(PSNR),Embedding Capacity(EC)and Structural Similarity Index Metric(SSIM).

关键词： Data hiding spatial correlation radix system prediction error embedding capacity

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Detection and Grading of Diabetic Retinopathy in Retinal Images Using Deep Intelligent Systems: A Comprehensive Review

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Computers, Materials & Continua 2021年第3期66卷 2771-2786页

作者： H.Asha Gnana Priya J.Anitha Daniela Elena Popescu Anju Asokan D.jude hemanth Le Hoang Son Department of ECE Karunya Institute of Technology and SciencesCoimbatore641114India Faculty of Electrical Engineering and Information Technology University of OradeaOradeaRomania Institute of Research and Development Duy Tan UniversityDa NangVietnam VNU Information Technology Institute Vietnam National UniversityHanoiVietnam

Diabetic Retinopathy(DR)is an eye disease that mainly affects people with *** affected by DR start losing their vision from an early stage even though the symptoms are identified only at the later *** the vision is lost,it cannot be regained but can be prevented from causing any further *** diagnosis of DR is required for preventing vision loss,for which a trained ophthalmologist is *** clinical practice is time-consuming and is not much successful in identifying DR at early ***,Computer-Aided Diagnosis(CAD)system is a suitable alternative for screening and grading of DR for a larger *** paper addresses the different stages in CAD system and the challenges in identifying and grading of DR by analyzing various recently evolved *** performance metrics used to evaluate the Computer-Aided Diagnosis system for clinical practice is also discussed.

关键词： Diabetic retinopathy computer-aided diagnosis system vessel extraction optic disc segmentation retinal features grading of DR

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