4 papers
SPaRSe-TIME: Saliency-Projected Low-Rank Temporal Modeling for Efficient and Interpretable Time Series Prediction
K. A. Shahriar
Time series forecasting is traditionally dominated by sequence-based architectures such as recurrent neural networks and attention mechanisms, which process all time steps uniforml…
Adaptive Temporal Dynamics for Personalized Emotion Recognition: A Liquid Neural Network Approach
Anindya Bhattacharjee, Nittya Ananda Biswas, K. A. Shahriar +1
Emotion recognition from physiological signals remains challenging due to their non-stationary, noisy, and subject-dependent characteristics. This work presents, to the best of our…
IoT-based Cost-Effective Fruit Quality Monitoring System using Electronic Nose
Anindya Bhattacharjee, Nittya Ananda Biswas, Khondakar Ashik Shahriar +1
Post-harvest losses due to subjective quality assessment cause significant damage to the economy and food safety, especially in countries like Bangladesh. To mitigate such damages,…
Why Nonlinear Models Matter: Unified Analysis of Cognitive Load, Stress, and Exercise Using Wearable Physiological Signals
Khondakar Ashik Shahriar
Wearable physiological signals exhibit strong nonlinear and subject-dependent behavior, challenging traditional linear models. This study provides a unified evaluation of cognitive…