Real-time pneumonia prediction using pipelined spark and high-performance computing

A Ravikumar, H Sriraman - PeerJ Computer Science, 2023 - peerj.com
Background Pneumonia is a respiratory disease caused by bacteria; it affects many people,
particularly in impoverished countries where pollution, unclean living standards …

Trojan Detection System Using Machine Learning Approach

MF Ab Razak, MI Jaya, Z Ismail… - Indonesian Journal of …, 2022 - ojs.uajy.ac.id
Malware attack cases continue to rise in our current day. The Trojan attack, which may be
extremely destructive by unlawfully controlling other users' computers in order to steal their …

Enhancing Trojan Detection using Machine Learning: Comparative Analysis of Classifier Performance on Embedded Hardware

R Parmar, N Gajjar - 2023 9th International Conference on …, 2023 - ieeexplore.ieee.org
In today's connected world, malware attacks, especially Trojan attacks are rapidly rising. A
Trojan is a form of malware that takes on a legitimate piece of software but is malicious and …

Circumventing Stragglers and Staleness in Distributed CNN using LSTM

A Ravikumar, H Sriraman, S Lokesh… - … Transactions on Internet …, 2024 - publications.eai.eu
INTRODUCTION: Using neural networks for these inherently distributed applications is
challenging and time-consuming. There is a crucial need for a framework that supports a …

Evaluation of the Distributed Strategies for Data Parallel Deep Learning Model in TensorFlow

A Ravikumar, H Sriraman - Scalable and Distributed Machine …, 2023 - igi-global.com
Distributed deep learning is a branch of machine intelligence in which the runtime of deep
learning models may be dramatically lowered by using several accelerators. Most of the past …

Single Node Acceleration of Generative Adversarial Networks using HPC for Image Analytics

A Ravikumar, H Sriraman - Proceedings of the 2022 5th International …, 2022 - dl.acm.org
Generative Adversarial Networks (GAN) are approaches that are utilized for data
augmentation, which facilitates the development of more accurate detection models for …

Enhancing Zero-Day Attack Detection with XAI-Driven ML Models and SMOTE Analysis

CK Sruthi, A Ravikumar… - 2024 3rd International …, 2024 - ieeexplore.ieee.org
Zero-day attacks, which are defined by their abrupt appearance without any previous
detection mechanisms, present a substantial obstacle in the field of network security. To …