Mahesh Banavar

11 papers B 1C 2Journal 7Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
A Hybrid Deep Learning Model for Robust Biometric Authentication from Low-Frame-Rate PPG Signals.
CoRR
Arfina Rahman, Mahesh Banavar
2025 J jnl
Development and Validation of SXI++ LNM Algorithm for Sepsis Prediction.
CoRR
Dharambir Mahto, Prashant Yadav, Mahesh Banavar, Jim Keany, Alan T. Joseph, Srinivas Kilambi
2024 J jnl
Deep Face Decoder: Towards understanding the embedding space of convolutional networks through visual reconstruction of deep face templates.
Eng. Appl. Artif. Intell.
Janez Krizaj, Richard Plesh, Mahesh Banavar, Stephanie Schuckers, Vitomir Struc
2024 B conf
Discovering Interpretable Feature Directions in the Embedding Space of Face Recognition Models.
IJCB
Richard Plesh, Janez Krizaj, Keivan Bahmani, Mahesh Banavar, Vitomir Struc, Stephanie Schuckers
2024 C conf
WIP: A Photoplethysmography Graphical User Interface for Teaching Signal Processing Concepts.
FIE
Mahesh Banavar, Olaoluwayimika Olugbenle, Logan Drake, Yemi Afolayanka, Arfina Rahman, Jianhua Zhang, Masudul Haider Imtiaz
2024 C conf
WIP: Comparison of Large Language Models for Applied Mathematics Questions in Engineering Courses.
FIE
Carlos Merlos, Faraz Hussain, Swati Kar, Lavanya Shri, Olaoluwayimika Olugbenle, Mahesh Banavar, Abd AlRahman AlMomani
2023 J jnl
A Novel Non-Linear Transformation Based Multi User Identification Algorithm for Fixed Text Keystroke Behavioral Dynamics.
IEEE Trans. Biom. Behav. Identity Sci.
Chinmay Sahu, Mahesh Banavar, Stephanie Schuckers
2023 J jnl
Data-Driven Nonlinear TDOA for Accurate Source Localization in Complex Signal Dynamics.
CoRR
Chinmay Sahu, Mahesh Banavar, Jie Sun
2023 — conf
Generalizability and Application of the Skin Reflectance Estimate Based on Dichromatic Separation (SREDS).
BIOSIG
Joseph Drahos, Richard Plesh, Keivan Bahmani, Mahesh Banavar, Stephanie Schuckers
2023 J jnl
Generalizability and Application of the Skin Reflectance Estimate Based on Dichromatic Separation (SREDS).
CoRR
Joseph Drahos, Richard Plesh, Keivan Bahmani, Mahesh Banavar, Stephanie Schuckers
2022 J jnl
How fragile is your network? More than you think.
CoRR
Jeremie Fish, Mahesh Banavar, Erik M. Bollt