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A project that utilized the Stationary Wavelet Transform for denoising signals
Проект по разметке сердечного цикла, основанный на управлемой специализации подсетей
(ImageNet pretrained models) The official pytorch implemention of the TPAMI paper "Res2Net: A New Multi-scale Backbone Architecture"
Automatic speech recognition for the Nepali language using CNN, bidirectional LSTM and ResNet - IEEE (ICICT - 2022)
[Biomedical Signal Processing and Control] ECGTransForm: Empowering adaptive ECG arrhythmia classification framework with bidirectional transformer
Full HRV analysis of Arduino pulse sensor, using Python signal processing and time series techniques. Chaotic, Fourier, Wavelet, Regression, Neural Net.
A Matlab toolbox for cardiovascular signal processing
A collection of deep learning models for ECG data processing based on fairseq framework
The work carried out in this project is in relation to my master's degree thesis. The project involves the task of analysing the data coming from Photoplethysmogram (PPG) and a single-lead Electroc…
Intelligent Heart Monitoring System (IHMS) for real-time arrhythmia detection - Queen's University ELEC490 Capstone Project
A MATLAB implementation of a robust QRS-detection algorithm for arrhythmia monitoring, with enhancements to improve accuracy and performance.
Developing a system capable of accurately classifying electrocardiogram (ECG) signals into three categories: arrhythmia, congestive heart failure (CHF), and normal sinus rhythm (NSR). We aim to enh…
An AI-driven Cardiovascular Monitoring and Arrhythmia Detection System
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials,…
Lecture Content for Data Science, Leadership and Management in Tech, Software Engineering, CyberSecurity, Digital Management and Cloud Web Development
A Data Engineering & Machine Learning Knowledge Hub
专注大数据学习面试，大数据成神之路开启。Flink/Spark/Hadoop/Hbase/Hive...
Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network