Rabiul Islam (rabiul-ai)

rabiul-ai

Geek Repo

Company:Texas A&M University

Location:Doha, Qatar

Home Page:https://sites.google.com/view/rabiuleeekuet/home

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Rabiul Islam's repositories

Arrhythmia_Classification

CNN-LSTM and Attention based Hybrid Model for ECG Arrhythmia Classification

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opencv-course

Learn OpenCV in 4 Hours - Code used in my Python and OpenCV course on freeCodeCamp.

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camus_challenge

This repository hosts all the code and information related to CAMUS challenge.

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cnn-imi

This is a repository for the code developed to produced the results in the paper "Detection of Inferior Myocardial Infarction using Shallow Convolutional Neural Networks" (https://arxiv.org/abs/1710.01115v3)

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DL-ECG-Review

A Review of Deep Learning Methods on ECG Data

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dynamic

EchoNet-Dynamic is a deep learning model for assessing cardiac function in echocardiogram videos.

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ecg-classification

Code for training and evaluating CNNs to classify ECG signals from the MIT-BIH arrhythmia database.

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ETAB

A Benchmark Suite for Visual Representation Learning in Echocardiography

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Graph-Machine-Learning

Graph Machine Learning, published by Packt

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LungNoduleDetectionClassification

Automated Extraction and Classification of Pulmonary Lung Nodules from CT Scans

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matplotlib_tutorial

Source code to go along with my tutorial to learn data visualization with the matplotlib library of Python

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medical-imaging-datasets

A list of Medical imaging datasets.

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mit-bih_ecg_recognition

MIT-BIH ECG data recognition using 1d CNN with tensorflow2

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MNIST-digit-classification

This code can classify 10 handwritten digit by simple neural network using Pytorch

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opencv

Open Source Computer Vision Library

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openface

Face recognition with deep neural networks.

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pandas

Data & Code for my video on the Pandas library of Python

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pytorchTutorial

PyTorch Tutorials from my YouTube channel

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rabiul-ai

Config files for my GitHub profile.

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repo1

Firstly testing to create a repo

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tmed2-echocardiogram-classifiers

Code for classification of echocardiograms (view type, severity level) with the TMED dataset

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Zero-Shot-ECG

A Personalized Zero-Shot ECG Anomaly Monitoring System: From Sparse Representation Based Domain Adaption to Energy Efficient Suspicious Beat Detection for a Practical ECG Surveillance

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