An Abstraction-Refinement Approach to Verifying Convolutional Neural Networks. (arXiv:2201.01978v1 [cs.LG])

Convolutional neural networks have gained vast popularity due to their
excellent performance in the fields of computer vision, image processing, and
others. Unfortunately, it is now well known that convolutional networks often
produce erroneous results - for example, minor perturbations of the inputs of
these networks can result in severe classification errors. Numerous
verification approaches have been proposed in recent years to prove the absence
of such errors, but these are typically geared for fully connected networks and
suffer from …

arxiv convolutional neural networks networks neural networks