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Time and Frequency Synergy for Source-Free Time-Series Domain Adaptations
Muhammad Tanzil Furqon, Mahardhika Pratama, Ary Mazharuddin Shiddiqi +3
The issue of source-free time-series domain adaptations still gains scarce research attentions. On the other hand, existing approaches rely solely on time-domain features ignoring…
PIP: Prototypes-Injected Prompt for Federated Class Incremental Learning
Muhammad Anwar Ma'sum, Mahardhika Pratama, Savitha Ramasamy +3
Federated Class Incremental Learning (FCIL) is a new direction in continual learning (CL) for addressing catastrophic forgetting and non-IID data distribution simultaneously. Exist…
Unsupervised Few-Shot Continual Learning for Remote Sensing Image Scene Classification
Muhammad Anwar Ma'sum, Mahardhika Pratama, Ramasamy Savitha +3
A continual learning (CL) model is desired for remote sensing image analysis because of varying camera parameters, spectral ranges, resolutions, etc. There exist some recent initia…
Mixup Domain Adaptations for Dynamic Remaining Useful Life Predictions
Muhammad Tanzil Furqon, Mahardhika Pratama, Lin Liu +2
Remaining Useful Life (RUL) predictions play vital role for asset planning and maintenance leading to many benefits to industries such as reduced downtime, low maintenance costs, e…
Dynamic Long-Term Time-Series Forecasting via Meta Transformer Networks
Muhammad Anwar Ma'sum, MD Rasel Sarkar, Mahardhika Pratama +5
A reliable long-term time-series forecaster is highly demanded in practice but comes across many challenges such as low computational and memory footprints as well as robustness ag…