Track Image Deltas

[Micky774]

Instead of analyzing the raw underlying image (either via GCNNs or other classification/representation strategies), use the deltas between frames -- that is to say, track how much each pixel changes in intensity form one frame to the next. This essentially transforms it into a task regarding modeling the first derivative which is likely a better indicator of motion-based phenotypes and morphologies in the first place. This may make the graph construction unstable, however for tasks such as classification, it may make it entirely unnecessary as well. See implementing a ResNet-style CNN on either individual deltas, or the net delta between first/last frames.

[Micky774]

Furthermore, we can consider employing some form of one-shot or few-shot out-of-distribution detection model on the deltas to detect the temporal signature of significant events.