Is there a way to update the neural network to fit the new data without the time required for retraining?

Question

I built a basic neural network in MATLAB. The neural network classifies points on the X-Y axis system into two classes (0 and 1).

(I try to get the function that represents a shape from this photo)

Every so often the values ​​of the points change slightly and some of the points defined in class 1 become class 0, like in this photo.

Is there a way to update the neural network to fit the new data without the time required for retraining?

Answer 1

If I understand your question, you want it to generalize to be conditioned on an image. If this is correct, you can do this via inserting a separate portion of the model that takes the image as an input, and compresses it into a dense feature vector (can be done many ways- most common is probably cnn) and then merge with the other inputs (in your case x,y pairs) and have the model train on that end-to-end.