Projects
An Optimal Deep Learning Framework for Detecting Abnormal Heartbeats Using ECG Signals
Research Project
The following project detects abnormal heartbeats using Electrocardiogram (ECG) signals. A Convolutional Neural Network is used to predict if the given heartbeat has arrhythmia using a 6-second window.
SMART GARBAGE MONITORING AND DISPOSAL SYSTEM
PAPER ACCEPTED BY THE IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA PROCESSING, COMMUNICATION AND
INFORMATION TECHNOLOGY – MPCIT 2020
This work demonstrates a Deep learning and IoT based solution for predicting and analyzing garbage level trends so that municipal authorities can undertake necessary steps to collect waste. Moreover, garbage level trends can be used for developing efficient strategies to reduce the amount of waste generated.
Feature Extraction for Hypoglycemic events detection based on ECG using
Transfer Learning
VII SEM B.E (ECE) NOV 2020 SEMINAR REPORT
In this study, we demonstrate how transfer learning can be applied to the ECG domain for early detection of Hypoglycemic events. Our model was trained using the ImageNet dataset, and features maps were transferred to extract patterns of small ECG excerpts.
