نتایج جستجو برای: Heart Sound Classification Deep Learning Neural Networks Self

تعداد نتایج: 2577770  

Introduction: Recent studies have acknowledged the potential of convolutional neural networks (CNNs) in distinguishing healthy and morbid samples by using heart sound analyses. Unfortunately the performance of CNNs is highly dependent on the filtering procedure which is applied to signal in their convolutional layer. The present study aimed to address this problem by a...

In this paper, we focus on two basic issues: (a) the classification of sound by neural networks based on frequency and sound intensity parameters (b) evaluating the health of different human ears as compared to of those a healthy person. Sound classification by a specific feed forward neural network with two inputs as frequency and sound intensity and two hidden layers is proposed. This process...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه علامه طباطبایی - دانشکده اقتصاد 1393

due to extraordinary large amount of information and daily sharp increasing claimant for ui benefits and because of serious constraint of financial barriers, the importance of handling fraud detection in order to discover, control and predict fraudulent claims is inevitable. we use the most appropriate data mining methodology, methods, techniques and tools to extract knowledge or insights from ...

Introduction: Electrocardiogram (ECG) is a method to measure the electrical activity of the heart which is performed by placing electrodes on the surface of the body. Physicians use observation tools to detect and diagnose heart diseases, the same is performed on ECG signals by cardiologists. In particular, heart diseases are recognized by examining the graphic representation of heart signals w...

Introduction: Electrocardiogram (ECG) is a method to measure the electrical activity of the heart which is performed by placing electrodes on the surface of the body. Physicians use observation tools to detect and diagnose heart diseases, the same is performed on ECG signals by cardiologists. In particular, heart diseases are recognized by examining the graphic representation of heart signals w...

Journal: :IEEE/ACM Transactions on Audio, Speech, and Language Processing 2015

2001
I. TURKOGLU A. ARSLAN

In this study, we develop a new automated pattern recognition system for interpretation of heart sound based on wavelet decomposition of signals and classification using neural network. Inputs to the system are the heart sound signals acquired by a stethoscope in a noiseless environment. We generate features for the objective concise representation of heart sound signals by means of wavelet dec...

Commercial quadcopters with many private, commercial, and public sector applications are a rapidly advancing technology. Currently, there is no guarantee to facilitate the safe operation of these devices in the community. Three different automatic commercial quadcopters identification methods are presented in this paper. Among these three techniques, two are based on deep neural networks in whi...

Journal: :نشریه دانشکده فنی 0
شبنم شهبازی دانشگاه صنعتی امیرکبیر عبدالرحیم جواهریان موسسه ژئوفیزیک مجتبی محمدو خراسانی شرکت ملی نفت

geological facies interpretation is essential for reservoir studying. the method of classification and identification seismic traces is a powerful approach for geological facies classification and distinction. use of neural networks as classifiers is increasing in different sciences like seismic. they are computer efficient and ideal for patterns identification. they can simply learn new algori...

ژورنال: محاسبات نرم 2019

Heart is one of the most important members of the body, and heart disease is the major cause of death in the world and Iran. This is why the early/on time diagnosis is one of the significant basics for preventing and reducing deaths of this disease. So far, many studies have been done on heart disease with the aim of prediction, diagnosis, and treatment. However, most of them have been mostly f...

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