International Business Machines Corporation

Takehiro Wakabayashi

Shingo Nagai

A training dataset including a plurality of labeled images can be received, each labeled image of the plurality of labeled images including a label represented by a bounding box having a designated class name. Characteristics of each label can be obtained. Statistical information for each class name of the plurality of labeled images can be determined based on the characteristics of each label associated with each respective class name. An outlier test can be performed based on the determined statistical information for a first designated class name to receive at least one outlier label having the first designated class name. The at least one outlier label can be output as a modification candidate for re-labeling.

Image recognition training data quality enhancement

An apparatus, a method, and computer program product are provided that tracks data for, and generated by, machine learning for accurate and precise deletion. The method includes receiving a dataset for use in training a machine learning model and registering a file from the dataset into a reference table, wherein the file is designated for monitoring. The file designation can indicate that the file is confidential and requires deletion upon completion of training of the machine learning model and project. The method also includes monitoring the file for an event that accesses the file, detecting a read access event occurring on the file, and determining a creation of a derivative file generated as a result of the read access event. The method further includes registering the derivative file into the reference table and indicating an association between the derivative file and the file in the reference table.

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Tokyo, Japan

Takehiro Wakabayashi