Google patents method to pack multiple images into one sequence for AI training
Google describes a way to train image-processing neural networks by combining pieces of several images into a single data stream. This approach allows the system to process multiple images together, potentially making the training process more efficient.
In the filing’s own words
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training an image processing neural network. For example, a method can include obtaining a batch of training examples, each training example comprising a respective training image; generating one or more input sequences, wherein each input sequence corresponds to two or more of the training images in the batch and is a sequence of tokens that comprises tokens representing patches from two or more corresponding training images; and processing each input sequence using the image processing neural network to generate a respective training output for each corresponding training image; and training the image processing neural network on a first loss function for the first task using the training outputs for the training images in the batch.
What exactly they claim (claim 1)
1. A method performed by one or more computers and for training an image processing neural network having image processing neural network parameters to perform a first task, the method comprising, at each of a plurality of training steps: obtaining a batch of training examples, each training example comprising a respective training image; for each training image: dividing the training image into a respective plurality of patches; and generating a respective token representing each of the patches; generating one or more input sequences, wherein each input sequence corresponds to two or more of the training images in the batch and is a sequence of tokens that comprises tokens representing patches from two or more corresponding training images; processing each input sequence using the image processing neural network to generate a respective training output for each corresponding training image; and training the image processing neural network on a first loss function for the first task using the training outputs for the training images in the batch.
Facts
- Company
- Google (Google LLC)
- Official title
- SEQUENCE PACKING FOR TRAINING IMAGE PROCESSING NEURAL NETWORKS
- Publication number
- US20260311467A1
- Application number
- 19485182
- Filed
- May 17, 2024
- Published
- Oct 8, 2026
- Inventors
- 4
- Claims
- 24
Classified under
G06V 10/774 Physics & computingG06V 10/764 Physics & computingG06V 10/82 Physics & computingMore from Google in AI & software
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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.