UniJDOT is a new optimal-transport method for universal domain adaptation on time series that accounts for unknown target samples in the transport cost, adds a joint decision space and auto-thresholding, and uses a Fourier layer to reach state-of-the-art performance.
A probabilistic hough transform,
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An end-to-end YOLOv11-based pipeline digitizes paper ECG images into calibrated 12-lead signals on CPU-only hardware in under 30 seconds and classifies myocardial infarction with up to 95.5% accuracy on PTB-XL and 88.9% on ECG-Matrix.
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Deep Joint Distribution Optimal Transport for Universal Domain Adaptation on Time Series
UniJDOT is a new optimal-transport method for universal domain adaptation on time series that accounts for unknown target samples in the transport cost, adds a joint decision space and auto-thresholding, and uses a Fourier layer to reach state-of-the-art performance.
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ECGLight: Compute-Light Framework For Paper ECG Digitization and Myocardial Infarction Screening
An end-to-end YOLOv11-based pipeline digitizes paper ECG images into calibrated 12-lead signals on CPU-only hardware in under 30 seconds and classifies myocardial infarction with up to 95.5% accuracy on PTB-XL and 88.9% on ECG-Matrix.