6 papers
CARNet Cycle-Conditioned Core Aggregation and Redistribution for Multivariate Time Series Forecasting
Awsaf Tausif Adib, Md. Shahria Sarker Shuvo, Md. Estehaar Ahmed Emon +4
Accurately modeling cross-variate dependencies remains a key challenge in multivariate time series forecasting, particularly in the presence of strong periodic patterns. Many exist…
A Point Cloud Transformer for Remote Monitoring and Automated Assessment of Physical Rehabilitation Exercises
Kazi Rafat, Md. Ismail Hossain, M M Lutfe Elahi +4
Rehabilitation exercises are essential in restoring lost physical functions of patients suffering from various diseases (e.g., Parkinson's, back pain). Carrying out these rehabilit…
One Step Closer to Ground Truth: A Multi-Scale Residual-Aware Representation Learning Pipeline for Predicting Time Series Data
Amrijit Biswas, Mustafa Kamal, Robin Krambroeckers +4
Transformer-based models have emerged as leading paradigms in time-series forecasting in recent years, employing self-attention mechanisms to capture long-range dependencies. Despi…
Shadow loss: Memory-linear deep metric learning for efficient training
Alif Elham Khan, Mohammad Junayed Hasan, Humayra Anjum +1
Deep metric learning objectives (e.g., triplet loss) require storing and comparing high-dimensional embeddings, making the per-batch loss buffer scale as , where i…
Predicting life satisfaction using machine learning and explainable AI
Alif Elham Khan, Mohammad Junayed Hasan, Humayra Anjum +2
Life satisfaction is a crucial facet of human well-being. Hence, research on life satisfaction is incumbent for understanding how individuals experience their lives and influencing…
HadaSmileNet: Hadamard fusion of handcrafted and deep-learning features for enhancing facial emotion recognition of genuine smiles
Mohammad Junayed Hasan, Nabeel Mohammed, Shafin Rahman +1
The distinction between genuine and posed emotions represents a fundamental pattern recognition challenge with significant implications for data mining applications in social scien…