Significance Single molecule real-time (SMRT) sequencing theoretically offers the opportunity to directly assess certain base modifications of native DNA molecules without any prior chemical/enzymatic conversions and PCR amplification, using kinetic signals of a DNA polymerase. However, the kinetic signal changes caused by 5mC modification are extremely subtle. Hence, the robust genome-wide measurement of 5mC modification has not been achieved. We enhanced 5mC detection using SMRT sequencing by holistically analyzing kinetic signals of a DNA polymerase and sequence context for every base within a measurement window. We employed a convolutional neural network to train a methylation classification model, leading to genome-wide 5mC detection. The sensitivity and specificity reached 90% and 94%, with a 99% correlation of overall methylation level with bisulfite sequencing.