[jononor]

You mean to get either 0-9 or 'no number'? Here are two approaches:

1) Integrated. Represent 'no number' as class number 11 in the original model. Retrain it with this additional class (needs additional training data).

2) Cascading. Train a dedicated model for 'number' versus 'no number' (binary classifier), and use that in front of the original model.

Note that the MNIST data comes already extracted from original image, centered in fixed-size images of 28x28 pixels. In a practical ML application these steps would also need to be done before classification can be performed.

[jononor]

In the work shown in the article, the segmentation and centering of digits looks to be done by the user holding the camera. Which can be workable for some applications!