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Time matters the most in medical diagnosis. Therefore, ECG has been extensively used in diagnosis and precise identification of several cardiac conditions. As continuation to the previous work, which concerned about feature extraction and classification of ECG signals applying CNN on distinct datasets, this paper presents residual learning model that makes training of networks easier and substantially deeper since the deeper neural networks are difficult to train. The proposed solution isdoi:10.29042/2020-10-5-81-86 fatcat:bsdthto5ljhtnhr6t5bkpjlj6a