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Found 7 papers, 0 papers with code
Beyond LoRA: Exploring Efficient Fine-Tuning Techniques for Time Series Foundational Models
Time Series Foundation Models (TSFMs) have recently garnered attention for their ability to model complex, large-scale time series data across domains such as retail, finance, and transportation.
Low-Rank Adaptation of Time Series Foundational Models for Out-of-Domain Modality Forecasting
We conduct comprehensive ablation studies to demonstrate the trade-offs between the number of tunable parameters and forecasting performance and assess the impact of varying LoRA matrix ranks on model performance.
Interpretable Vital Sign Forecasting with Model Agnostic Attention Maps
This paper introduces a framework that combines a deep learning model with an attention mechanism that highlights the critical time steps in the forecasting process, thus improving model interpretability and supporting clinical decision-making.
Remote Heart Rate Monitoring in Smart Environments from Videos with Self-supervised Pre-training
Recent advances in deep learning have made it increasingly feasible to estimate heart rate remotely in smart environments by analyzing videos.
Privacy-Preserving Remote Heart Rate Estimation from Facial Videos
Remote Photoplethysmography (rPPG) is the process of estimating PPG from facial videos.
Colorectal Cancer Segmentation using Atrous Convolution and Residual Enhanced UNet
Colorectal cancer is a leading cause of death worldwide.
Detector-SegMentor Network for Skin Lesion Localization and Segmentation
Segmentation of skin lesion is a crucial step in the classification of melanoma cancer from the cancerous lesions in dermoscopic images.
