minimal images for humans in several aspects, namely region size and location, and frequency and sharpness of the drop in accuracy. We find that a slight adjustment of a one-pixel shift or two-pixel shrink of the visible image region produces a drop in DNN recognition accuracy in many image regions. Figure \[fig:DNNMinImgExample\] shows several examples of minimal image analogs of state-of-the-art DNNs.

The adjustments of the visible area that affect DNNs are almost indistinguishable to humans and can occur in larger regions than the “human minimal” region. To describe this phenomenon we introduce *fragile recognition images (FRIs)* for DNNs, which are more general than minimal images:

[**Fragile Recognition Image (FRI):**]{} *A fragile recognition image is a region of an image for which a slight change of the region’s size or location in the image produces a large change in DNN recognition output.*

This definition is more general than the definition of minimal images for humans, as the latter is included in the definition for DNNs. Minimal images are the case of fragile recognition in which the slight change is a reduction in the size of the region, and the minimal image is one of the smallest possible FRIs. In human 