Patent ID: 11948382
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method comprising:
receiving, by one or more computer processors, a set of dictates associated with generating one or more negative training datasets for training a set of models to classify a plurality of features found within a data source;
identifying, by one or more computer processors, a set of rules related to generating negative training data to detect text based on the received set of dictates;
compiling, by one or more computer processors, one or more arrays of elements of hard-negative training data into a negative training data dataset based on the identified set of rules and one or more dictates, an element of the hard-negative training data generated based on a character corresponding to a language and an identified first rule, further comprising:
selecting, by one or more computer processors, a random character;
rendering, by one or more computer processors, the selected character within a tile of a dictated size;
partitioning, by one or more computer processors, the tile into two or more segments, wherein at least one segment of the two or more segments includes a portion of the rendered character; and
modifying, by one or more computer processors, a portion of the rendered character included within a respective segment utilizing one or more effects; and

determining, by one or more computer processors, metadata corresponding an array of elements of hard-negative training data.