Cuffless blood pressure estimation through convolutional neural network regressor.

The dataset used for the "Non-Contact Blood Pressure Estimation using infrared motion magnified facial video" publication. The code developed is to fit the data to the reference Blood Pressure values.

long-term blood pressure prediction with deep recurrent neural networks

Predicting blood pressure from rPPG signal using LSTMs

Feature Extraction from Photoplethysmography

This consist of basic examples of performing Speech Recognition in Python using Google Speech Recognition Engine

Multi-threading camera stream to improve video processing performance

Multiple Camera CCTV/RTSP/Video Streaming with Flask and OpenCV

Fetch RTSP Stream using GStreamer in Python and get image in Numpy

predicting the buggy source files from the bug reports.

This Repository includes all the computer assignments which are designed by me as the TA in "Applied Data Science" course

We conduct a large-scale empirical study to understand better the impacts of textual dissimilarity on the detection of duplicate bug reports.

Lab that covers video conversion workflow for Video On Demand using AWS MediaConvert.

An anomaly detector that used an autoencoder to identify unusual ecg segments

Official implementation of "Regularised Encoder-Decoder Architecture for Anomaly Detection in ECG Time Signals"

Python code for African vulture optimization algorithm

Python code for Honey Badger Optimization Algorithm

Deep learning ECG models implemented using PyTorch

Machine learning-based prediction models with time-series data (1. ECG Signal Classification)

Classification of ecg signal using mitbih dataset

Python Notebooks with Supervised and Semi-Supervised Classification of ECG Data

ECG-Multi-class-classification-using-machine-learning

Creation of a model able to classify ECG (heart beats) into 5 classes from Normal ones to beats that cannot be classified at all.

👨‍💻 Developed AI Models - Ensemble of Random Forest & SVM and XGBoost classifiers to classify five types of Arrhythmic Heartbeats from ECG signals - published by IEEE.