Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Senthil Kumaran, Thangamuthu
Unknown Affiliation
Computer Science & IT Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
An auto-encoder bio medical signal transmission through custom convolutional neural network Muniraju, Usha; Senthil Kumaran, Thangamuthu
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp1312-1325

Abstract

The transmission of biomedical signals in real-time is extremely difficult and necessitates the use of cloud and internet of things (IoT) infrastructure. Security is also an important consideration, however, to achieve this, a reconstruction method is developed where the entire signal is fed as an input, just the primary portion, the entire signal is taken then encoded, and then deliver to the destination. It is unlocked using a reconstruction technique without any signal attenuation. The key difficulty is how to manage the sensor network once the input is prepared for transmission. This has problems with extremely high network energy consumption and accurate data collection. The accuracy of data reconstruction through is improved by compressive sensing. The lifespan of the network as a whole could be extended, in this study; the proposed proposed system convolutional neural network (PS-CNN) is an integrated model that combines feature selection and auto-encoder. In order to produce the most useful features for particular tasks, our algorithm can eventually separate the appropriate task units from the irrelevant tasks.
Co-Authors Muniraju, Usha