sathishprasad / Detecting-Anomaly-in-ECG-Data-Using-AutoEncoder-with-PyTorch
This project, "Detecting Anomaly in ECG Data Using AutoEncoder with PyTorch," focuses on leveraging an LSTM-based Autoencoder for identifying irregularities in ECG signals. It employs PyTorch to train and evaluate the model on datasets of normal and anomalous heart patterns, emphasizing real-time anomaly detection to enhance cardiac monitoring.
☆11Updated last year
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