Author

B. Stanley

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Conference Aug 2026

A Hybrid Deep Learning Approach for Emotion Recognition Using Gait Patterns, Body Gestures, and Facial Expressions

Human emotion recognition from visual cues has gained significant attention due to its applications in human-computer interaction, surveillance, and healthcare. However, relying on a single modality often limits the robustness of emotion understanding in real-world scenarios. To address this, we propose a novel hybrid...

R. J. R. Kumar, G. Brindha, S. Gayathri et al. · International Conference on... · 0 citations

Conference Aug 2026

Next-Gen IoT-Driven Real-Time Fuel Level Tracking and Optimization System

Businesses operational expenses are impacted by the incessantly rising cost of fuel. To stop gasoline theft, it’s a good idea to utilize a fuel tracking gadget that is made specifically to record information on fuel usage in real time and fuel replenishing themselves. Diesel generator and commercial vehicle operating c...

D. Shahila, Joel Livin, P. Jeyanthy et al. · International Conference on... · 0 citations

Conference Aug 2026

Automated Detection of Cerebral Microbleeds in Susceptibility-Weighted MRI Using a Multi-Scale Deep Learning Framework

Cerebral microbleeds (CMBs) are small hemosiderin deposits associated with cerebral small vessel disease and are considered important biomarkers for stroke risk, dementia, and neurodegenerative disorders. Manual identification of CMBs in susceptibility-weighted imaging (SWI) or T2*-weighted MRI is time-consuming and pr...

B. Stanley, R. J. R. Kumar, M. Ajisha et al. · International Conference on... · 0 citations

Conference Aug 2026

Transformer Based Modeling of Spatio Temporal Facial Dynamics for Micro-Expression Recognition

Micro-temporal facial expressions consist of brief and subtle muscle activations that convey genuine emotional states. Accurately modeling these transient dynamics is challenging due to their low intensity, short duration, and limited spatial variation, which often hinder the performance of conventional convolutional a...

J. R, K. Sindhubala, D. R. Angel Kiruba et al. · International Conference on... · 0 citations

Conference Aug 2026

Predicting Alzheimer’s Disease Progression from Mild Cognitive Impairment via Automated Brain Age Modeling

The early detection of individuals with Mild Cognitive Impairment (MCI) who are at high risk of developing Alzheimer’s Disease (AD) is important for proper clinical intervention and disease management. Studies show that there is a strong link between brain age, which is estimated from brain scan data, and actual chrono...

B. Stanley, K. Sindhubala, J. S. Shemona et al. · International Conference on... · 0 citations