How do I train a deep learning algorithm to find the template for an image and then compare other images to this template?
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Cai Chin on 19 Dec 2020
Commented: Cai Chin on 31 Dec 2020
Hi, I am using MATLAB R2020a on a MacOS. I am currently trying to detect abnormal phase-space trajectories in the 2D space on a cycle-by-cycle basis as part of an ECG signal. Is there any way of training an algorithm with 'normal' trajectories within that signal and then using this ground truth as a template against which to compare the trajectory associated with each new cycle to find and flag abnormal cycles? Within the signal, there would be mostly normal cycles with intermittent periods of abnormality.
Below is an example of what would constitute a 'normal' trajectory:
This is an example of an abnormal cycle, but abnormal trajectories have variable morphologies:
Please note though, that the comparison would not be against a fixed 'normal' template, but rather a normalised template for a particular individual's signal.
Any suggestions would be very much appreciated. Thanks in advance
Nikhil Sonavane on 22 Dec 2020
You may refer to the following documentation link for more details on it-
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