METHOD FOR WATERMARKING A MACHINE LEARNING MODEL

A method is provided for watermarking a machine learning model used for object detection. In the method, a first subset of a labeled set of ML training samples is selected. Each of one or more objects in the first subset includes a class label. A pixel pattern is selected to use as a watermark in th...

Full description

Saved in:
Bibliographic Details
Main Authors Schalij, Frederik Dirk, Michiels, Wilhelmus Petrus Adrianus Johannus
Format Patent
LanguageEnglish
Published 02.02.2023
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
PHYSICS
Online AccessGet full text

Cover

More Information
Summary:A method is provided for watermarking a machine learning model used for object detection. In the method, a first subset of a labeled set of ML training samples is selected. Each of one or more objects in the first subset includes a class label. A pixel pattern is selected to use as a watermark in the first subset of images. The pixel pattern is made partially transparent. A target class label is selected. One or more objects of the first subset of images are relabeled with the target class label. In another embodiment, the class labels are removed from objects in the subset of images instead of relabeling them. Each of the first subset of images is overlaid with the partially transparent and scaled pixel pattern. The ML model is trained with the set of training images and the first subset of images to produce a trained and watermarked ML model.
Bibliography:Application Number: US202117444108