US 2022/0092360 A1 · CONTRASTIVE EXPLANATIONS FOR IMAGES WITH MONOTONIC ATTRIBUTE FUNCTIONS

Abstract

In an embodiment, a method for generating contrastive information for a classifier prediction comprises receiving image data representative of an input image, using a deep learning classifier model to predict a first classification for the input image, evaluating the input image using a plurality of classifier functions corresponding to respective high-level features to identify one or more of the high-level features absent from the input image, and identifying, from among the high-level features absent from the input image, a pertinent-negative feature that, if added to the input image, will result in the deep learning classifier model predicting a second classification for the modified input image, the second classification being different from the first classification. In an embodiment, the method includes creating a pertinent-positive image that is a modified version of the input image that has the first classification and fewer than all superpixels of the input image.

Claims20

Dependent claims

A computer implemented method for generating contrastive information for a classifier prediction, the computer implemented method comprising:

receiving, by one or more processors, image data representative of an original input image;
creating, by the one or more processors, a modified input image by adding a high-level feature to a copy of the original input image;
and
determining, by the one or more processors, using a deep learning classifier model, that the modified input image is a pertinent-negative image that is most similar to the original input image in a set of modified input images, wherein the modified input image has a classification that is different from a classification of the original input image.

1 more element

A computer usable program product for generating contrastive information for a classifier prediction, the computer usable program product comprising a computer-readable storage device, and program instructions stored on the storage device, the stored program instructions comprising:

program instructions to receive, by one or more processors, image data representative of an original input image;
program instructions to create, by the one or more processors, a modified input image by adding a high-level feature to a copy of the original input image;
and
program instructions to determine, by the one or more processors, using a deep learning classifier model, that the modified input image is a pertinent-negative image that is most similar to the original input image in a set of modified input images, wherein the modified input image has a classification that is different from a classification of the original input image.

1 more element

Dependencies are inferred from the claim text.

Contrastive explanations for images with monotonic attribute functions

Life of this patent

Contrastive explanations for images with monotonic attribute functions

Life of this patent

Abstract

Claims20