Tejaswininnn

Tejaswininnn

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PyHook

PyHook is an offensive API hooking tool written in python designed to catch various credentials within the API call.

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CNNs-on-CHB-MIT

The project is about applying CNNs to EEG data from CHB-MIT to predict seizure

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keystroke-biometrics

Biometrics on Keystroke Dynamics

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keystroke_dynamics

a keystroke dynamics algorithm in python (recognizes a person by the way s/he types)

lung-sound-vggish

Implementation of IEEE Access paper - Lung Sound Recognition Algorithm Based on VGGish-BiGRU

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keystroke-dynamics

Demo to show keystroke dynamics / keystroke biometrics

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Anomaly-Detection-for-Keystroke-Dynamics

Comparing Anomaly-Detection Algorithms for Keystroke Dynamics based on http://www.cs.cmu.edu/~keystroke/

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User-Authentication-using-keystroke-dynamics

Using unique typing patterns (Keystroke Dynamics) of users as signature to authenticate user and classify user as genuine or imposter. For Methodology visit: https://www.nikhildagrawal.com/keystroke.html

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keystroke-dynamics-datagen

Generate dataset for keystroke timings for exploratory and research purposes.

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Parkinson-s-Disease-Classification-from-Speech-Data

Parkinson’s Disease Classification from Speech Data using multiple Machine Learning approaches. This was implemented using scikit-learn Python package.

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Keylogger

A Keylogger made in Python that sends you the collected data via email.

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BioKey---Keystroke-dynamics-for-user-authentication

Our project considers various machine learning and deep learning techniques like CNN and RNN based on free-text keystroke features for user authentication. Moreover, we will develop a simple UI to test new users.

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FYP-Keystroke-Dynamics

The Final Year Project on detecting anomalies using Keystroke Dynamics.

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LSTM-Epileptic-Seizure-Recognition

Epileptic seizure classification using a deep neural network (LSTM)

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Classification-Analysis-Of-Parkinson-Speech-Dataset

Repository For Machine Learning Final Project

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Disease-Diagnosis-and-Recommendation-System

A system that analyses patient symptoms and provides preliminary diagnoses along with recommended treatments⚕️

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KeyStroke-Dynamics

Keystroke dynamics refers to the automated method of identifying or confirming the identity of an individual based on the manner and the rhythm of typing on a keyboard

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BioKey-Keystrokes-dynamics-for-continuous-user-authentication

Continuous authentication of users by their interaction with the keyboard using keystrokes dynamics with deep learning

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ssl-seizure-detection

Self-supervised learning with graph neural network backbones for seizure detection in iEEG data.

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keystroke-stress

keystroke dynamics, mouse, other computer activities with stress sensing

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key-stroke-dynamics

User-Verification-based-on-Keystroke-Dynamics

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Keystroke_Dynamics_Gen

Generator of keystroke dynamics dataset

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Keyboard-Typing-User-Recognition

User recognition based on keyboard typing patterns using machine learning kNN algorithm.

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keystroke-dinamics

Typing dynamics project of the machine learning discipline.

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Brain_Disorder_Prediction

Epilepsey and Insomnia Detection Using EEG signals

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EEG-BASED-EPILEPTIC-SEIZURE-PREDICTION-USING-ENSEMBLE-LEARNING

This project focuses on predicting epileptic seizures using EEG signals and ensemble learning techniques. It aims to provide accurate and timely predictions to help individuals with epilepsy manage their condition more effectively.

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Keystroke-Biometric-Authentication-ML

Predicts users based on their typing pattern using ANN