G.V. Mahesh Vijayalakshmi

Vijayalakshmi G V Mahesh received her BE in Electronics and Communication Engineering from Bangalore University, India in 1999, and M.Tech in Digital Communication and Networking from Visvesvaraya Technological University in 2005 and the Ph.D. degree from the Vellore Institute of Technology, Vellore, India. Currently she is working as an Associate Professor at BMS Institute of Technology and Management, Bangalore, India. She has been in academics for over 19 years and has published her research in various reputed journals and conferences. Her research interests include Machine Learning, Image Processing, Pattern Recognition and Deep learning, Affective computing. She has Memberships in Professional Bodies such as ISTE and IEI.

Publications

Innovative Machine Learning Applications for Cryptography
Innovative Machine Learning Applications for Cryptography
J. Anitha Ruth, G.V. Mahesh Vijayalakshmi, P. Visalakshi, R. Uma, A. Meenakshi. © 2024. 294 pages.
Data security is paramount in our modern world, and the symbiotic relationship between machine learning and cryptography has recently taken center stage. The vulnerability of...
Machine Learning and Cryptographic Solutions for Data Protection and Network Security
Machine Learning and Cryptographic Solutions for Data Protection and Network Security
J. Anitha Ruth, Vijayalakshmi G. V. Mahesh, P. Visalakshi, R. Uma, A. Meenakshi. © 2024. 526 pages.
In the relentless battle against escalating cyber threats, data security faces a critical challenge – the need for innovative solutions to fortify encryption and decryption...
An Effective Combination of Pattern Recognition and Encryption Scheme for Biometric Authentication Systems
An Effective Combination of Pattern Recognition and Encryption Scheme for Biometric Authentication Systems
Vijayalakshmi G. V. Mahesh. © 2024. 21 pages.
Authentication based on biometric technology is largely preferred in providing access control to the systems. This technology has gained wider attention due to the rise in data...
Investigation of Deep Fake Images Using Pre-Trained CNN Frameworks
Investigation of Deep Fake Images Using Pre-Trained CNN Frameworks
Anitha Ruth J., Uma R., Vijayalakshmi G. V. Mahesh, P. Ramkumar. © 2022. 13 pages.
Deep learning technologies, such as neural networks, have tackled complicated issues from large-scale data processing to computer vision and human-level control. Editing...