-
公开(公告)号：US20240169715A1
公开(公告)日：2024-05-23
申请号：US18518075
申请日：2023-11-22
Applicant: GOOGLE LLC
Inventor： Lucas Klaus Beyer , Pavel Izmailov , Simon Kornblith , Alexander Kolesnikov , Mathilde Caron , Xiaohua Zhai , Matthias Johannes Lorenz Minderer , Ibrahim Alabdulmohsin , Michael Tobias Tschannen , Filip Pavetic
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a neural network that is configured to process an input image to generate a network output for the input image. In one aspect, a method comprises, at each of a plurality of training steps: obtaining a plurality of training images for the training step; obtaining, for each of the plurality of training images, a respective target output; and selecting, from a plurality of image patch generation schemes, an image patch generation scheme for the training step, wherein, given an input image, each of the plurality of image patch generation schemes generates a different number of patches of the input image, and wherein each patch comprises a respective subset of the pixels of the input image.
-
公开(公告)号：US20220383630A1
公开(公告)日：2022-12-01
申请号：US17829227
申请日：2022-05-31
Applicant: Google LLC
IPC: G06V10/82 , G06V10/774
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training Vision Transformer (ViT) neural networks.
-
公开(公告)号：US20220108478A1
公开(公告)日：2022-04-07
申请号：US17492537
申请日：2021-10-01
Applicant: Google LLC
Inventor： Neil Matthew Tinmouth Houlsby , Sylvain Gelly , Jakob D. Uszkoreit , Xiaohua Zhai , Georg Heigold , Lucas Klaus Beyer , Alexander Kolesnikov , Matthias Johannes Lorenz Minderer , Dirk Weissenborn , Mostafa Dehghani , Alexey Dosovitskiy , Thomas Unterthiner
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images using self-attention based neural networks. One of the methods includes obtaining one or more images comprising a plurality of pixels; determining, for each image of the one or more images, a plurality of image patches of the image, wherein each image patch comprises a different subset of the pixels of the image; processing, for each image of the one or more images, the corresponding plurality of image patches to generate an input sequence comprising a respective input element at each of a plurality of input positions, wherein a plurality of the input elements correspond to respective different image patches; and processing the input sequences using a neural network to generate a network output that characterizes the one or more images, wherein the neural network comprises one or more self-attention neural network layers.
-
公开(公告)号：US12125247B2
公开(公告)日：2024-10-22
申请号：US17492537
申请日：2021-10-01
Applicant: Google LLC
Inventor： Neil Matthew Tinmouth Houlsby , Sylvain Gelly , Jakob D. Uszkoreit , Xiaohua Zhai , Georg Heigold , Lucas Klaus Beyer , Alexander Kolesnikov , Matthias Johannes Lorenz Minderer , Dirk Weissenborn , Mostafa Dehghani , Alexey Dosovitskiy , Thomas Unterthiner
CPC classification number: G06T7/97 , G06F18/24 , G06N3/045 , G06N3/08 , G06T2207/20081 , G06T2207/20084
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images using self-attention based neural networks. One of the methods includes obtaining one or more images comprising a plurality of pixels; determining, for each image of the one or more images, a plurality of image patches of the image, wherein each image patch comprises a different subset of the pixels of the image; processing, for each image of the one or more images, the corresponding plurality of image patches to generate an input sequence comprising a respective input element at each of a plurality of input positions, wherein a plurality of the input elements correspond to respective different image patches; and processing the input sequences using a neural network to generate a network output that characterizes the one or more images, wherein the neural network comprises one or more self-attention neural network layers.
-
公开(公告)号：US20240062426A1
公开(公告)日：2024-02-22
申请号：US18500034
申请日：2023-11-01
Applicant: Google LLC
Inventor： Neil Matthew Tinmouth Houlsby , Sylvain Gelly , Jakob D. Uszkoreit , Xiaohua Zhai , Georg Heigold , Lucas Klaus Beyer , Alexander Kolesnikov , Matthias Johannes Lorenz Minderer , Dirk Weissenborn , Mostafa Dehghani , Alexey Dosovitskiy , Thomas Unterthiner
CPC classification number: G06T7/97 , G06F18/24 , G06N3/045 , G06N3/08 , G06T2207/20081 , G06T2207/20084
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images using self-attention based neural networks. One of the methods includes obtaining one or more images comprising a plurality of pixels; determining, for each image of the one or more images, a plurality of image patches of the image, wherein each image patch comprises a different subset of the pixels of the image; processing, for each image of the one or more images, the corresponding plurality of image patches to generate an input sequence comprising a respective input element at each of a plurality of input positions, wherein a plurality of the input elements correspond to respective different image patches; and processing the input sequences using a neural network to generate a network output that characterizes the one or more images, wherein the neural network comprises one or more self-attention neural network layers.
-
Patent Agency Ranking
公开(公告)号：US20220189612A1
公开(公告)日：2022-06-16
申请号：US17551050
申请日：2021-12-14
Applicant: Google LLC
Inventor： Xiaohua Zhai , Sylvain Gelly , Alexander Kolesnikov , Yin Ching Jessica Yung , Joan Puigcerver i Perez , Lucas Klaus Beyer , Neil Matthew Tinmouth Houlsby , Wen Yau Aaron Loh , Alan Prasana Karthikesalingam , Basil Mustafa , Jan Freyberg , Patricia Leigh MacWilliams , Vivek Natarajan
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network to perform a downstream computer vision task. One of the methods includes pre-training an initial neural network that shares layers with the neural network to perform an initial computer vision task and then training the neural network on the downstream computer vision task.
-
公开(公告)号：US20250005798A1
公开(公告)日：2025-01-02
申请号：US18883946
申请日：2024-09-12
Applicant: Google LLC
Inventor： Neil Matthew Tinmouth Houlsby , Sylvain Gelly , Jakob D. Uszkoreit , Xiaohua Zhai , Georg Heigold , Lucas Klaus Beyer , Alexander Kolesnikov , Matthias Johannes Lorenz Minderer , Dirk Weissenborn , Mostafa Dehghani , Alexey Dosovitskiy , Thomas Unterthiner
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images using self-attention based neural networks. One of the methods includes obtaining one or more images comprising a plurality of pixels; determining, for each image of the one or more images, a plurality of image patches of the image, wherein each image patch comprises a different subset of the pixels of the image; processing, for each image of the one or more images, the corresponding plurality of image patches to generate an input sequence comprising a respective input element at each of a plurality of input positions, wherein a plurality of the input elements correspond to respective different image patches; and processing the input sequences using a neural network to generate a network output that characterizes the one or more images, wherein the neural network comprises one or more self-attention neural network layers.
-
公开(公告)号：US20250005797A1
公开(公告)日：2025-01-02
申请号：US18883917
申请日：2024-09-12
Applicant: Google LLC
Inventor： Neil Matthew Tinmouth Houlsby , Sylvain Gelly , Jakob D. Uszkoreit , Xiaohua Zhai , Georg Heigold , Lucas Klaus Beyer , Alexander Kolesnikov , Matthias Johannes Lorenz Minderer , Dirk Weissenborn , Mostafa Dehghani , Alexey Dosovitskiy , Thomas Unterthiner
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images using self-attention based neural networks. One of the methods includes obtaining one or more images comprising a plurality of pixels; determining, for each image of the one or more images, a plurality of image patches of the image, wherein each image patch comprises a different subset of the pixels of the image; processing, for each image of the one or more images, the corresponding plurality of image patches to generate an input sequence comprising a respective input element at each of a plurality of input positions, wherein a plurality of the input elements correspond to respective different image patches; and processing the input sequences using a neural network to generate a network output that characterizes the one or more images, wherein the neural network comprises one or more self-attention neural network layers.
-
公开(公告)号：US20220375211A1
公开(公告)日：2022-11-24
申请号：US17737507
申请日：2022-05-05
Applicant: Google LLC
Inventor： Ilya Tolstikhin , Neil Matthew Tinmouth Houlsby , Alexander Kolesnikov , Lucas Klaus Beyer , Alexey Dosovitskiy , Mario Lucic , Xiaohua Zhai , Thomas Unterthiner , Daniel M. Keysers , Jakob D. Uszkoreit , Yin Ching Jessica Yung , Andreas Steiner
IPC: G06V10/82 , G06V10/764 , G06N3/04
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images using mixer neural networks. One of the methods includes obtaining one or more images comprising a plurality of pixels; determining, for each image of the one or more images, a plurality of image patches of the image, wherein each image patch comprises a different subset of the pixels of the image; processing, for each image of the one or more images, the corresponding plurality of image patches to generate an input sequence comprising a respective input element at each of a plurality of input positions, wherein a plurality of the input elements correspond to respective different image patches; and processing the input sequences using a neural network to generate a network output that characterizes the one or more images, wherein the neural network comprises one or more mixer neural network layers.
-
公开(公告)号：US12272442B2
公开(公告)日：2025-04-08
申请号：US17551050
申请日：2021-12-14
Applicant: Google LLC
Inventor： Xiaohua Zhai , Sylvain Gelly , Alexander Kolesnikov , Yin Ching Jessica Yung , Joan Puigcerver i Perez , Lucas Klaus Beyer , Neil Matthew Tinmouth Houlsby , Wen Yau Aaron Loh , Alan Prasana Karthikesalingam , Basil Mustafa , Jan Freyberg , Patricia Leigh MacWilliams , Vivek Natarajan
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network to perform a downstream computer vision task. One of the methods includes pre-training an initial neural network that shares layers with the neural network to perform an initial computer vision task and then training the neural network on the downstream computer vision task.
-
-
-
-
-
-
-
-
-
Search Results
12
records
(took 0.013 seconds)
