International Business Machines Corporation
IDENTIFYING A TYPE OF OBJECT IN A DIGITAL IMAGE BASED ON OVERLAPPING AREAS OF SUB-IMAGES

Abstract:

A method identifies a type of object in a digital image. A user and/or one or more processors selects, from a plurality of partially overlapping sub-images of a digital image, a first sub-image and a second sub-image that overlap one another. The user/processors input the first sub-image into a neural network to create a first inference result that includes an overlapping inference result, for the overlapping area, that recognizes a partial portion of a specific type of object based on the overlapping area. The user/processors infer that the second sub-image creates a second inference result that recognizes a second portion of the specific type of object in the second sub-image based on the second sub-image and the overlapping inference result. The neural network identifies the specific type of object in the digital image based on the first and second sub-images being sub-images of a same type of object.