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This question is more related to signal processing than to computer vision since the input in 1D. Anyway, there is a large number of potential methods that you can use. For practical reason, I would start by obvious choices (detection of maximum in signal). If the noise in the data does not allow to use it, you should think how to model the noise. This can be done either by encoding it manually or learning the expected variations from training data. What kind of signal is it by the way?