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e-G2C: A 0.14-to-8.31 μJ/Inference NN-based Processor with Continuous On-chip Adaptation for Anomaly Detection and ECG Conversion from EGM.

, , , , , , , , , , , , and . CoRR, (2022)

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Acoustic Detection of Coronary Occlusions before and after Stent Placement Using an Electronic Stethoscope., , , , , , , and . Entropy, 18 (8): 281 (2016)RT-RCG: Neural Network and Accelerator Search Towards Effective and Real-time ECG Reconstruction from Intracardiac Electrograms., , , , , , , , and . ACM J. Emerg. Technol. Comput. Syst., 18 (2): 29:1-29:25 (2022)e-G2C: A 0.14-to-8.31 µJ/Inference NN-based Processor with Continuous On-chip Adaptation for Anomaly Detection and ECG Conversion from EGM., , , , , , , , , and 3 other author(s). VLSI Technology and Circuits, page 252-253. IEEE, (2022)A novel convolutional neural network for reconstructing surface electrocardiograms from intracardiac electrograms and vice versa., , , , , , and . Artif. Intell. Medicine, (2021)Graph-Based Interpolation of Local Activation Time on the Cardiac Surface., , , , , , and . ACSCC, page 274-278. IEEE, (2021)A Novel Method for 12-Lead ECG Reconstruction., , , , and . ACSSC, page 1054-1058. IEEE, (2023)e-G2C: A 0.14-to-8.31 μJ/Inference NN-based Processor with Continuous On-chip Adaptation for Anomaly Detection and ECG Conversion from EGM., , , , , , , , , and 3 other author(s). CoRR, (2022)