公开(公告)号：US11755948B2

公开(公告)日：2023-09-12

申请号：US16719244

申请日：2019-12-18

Applicant: Google LLC

Inventor： Andrei Kapishnikov ,  Tolga Bolukbasi ,  Fernanda Bertini Viégas ,  Michael Andrew Terry

IPC: G06N20/00 ,  G06N5/04 ,  G06N20/10

CPC classification number: G06N20/00 ,  G06N5/04 ,  G06N20/10

Abstract: Methods, systems, devices, and tangible non-transitory computer readable media for saliency visualization are provided. The disclosed technology can include receiving a data input including a plurality of features. The data input can be segmented into regions. At least one of the regions can include two or more of the features. Attribution scores can be respectively generated for features of the data input. The attribution scores for each feature can be indicative of a respective saliency of such feature. A respective gain value for each region can be determined over one or more iterations based on the respective attribution scores associated with the features included in the region. Further, at each iteration one or more of the regions with the greatest gain values can be added to a saliency mask. Furthermore, at each iteration a saliency visualization can be produced based on the saliency mask.

公开(公告)号：US12236326B2

公开(公告)日：2025-02-25

申请号：US18363277

申请日：2023-08-01

Applicant: Google LLC

Inventor： Andrei Kapishnikov ,  Fernanda Bertini Viégas ,  Michael Andrew Terry ,  Tolga Bolukbasi

IPC: G06N20/00 ,  G06N5/04 ,  G06N20/10

Abstract: Methods, systems, devices, and tangible non-transitory computer readable media for saliency visualization are provided. The disclosed technology can include receiving a data input including a plurality of features. The data input can be segmented into regions. At least one of the regions can include two or more of the features. Attribution scores can be respectively generated for features of the data input. The attribution scores for each feature can be indicative of a respective saliency of such feature. A respective gain value for each region can be determined over one or more iterations based on the respective attribution scores associated with the features included in the region. Further, at each iteration one or more of the regions with the greatest gain values can be added to a saliency mask. Furthermore, at each iteration a saliency visualization can be produced based on the saliency mask.

公开(公告)号：US20240054402A1

公开(公告)日：2024-02-15

申请号：US18363277

申请日：2023-08-01

Applicant: Google LLC

Inventor： Andrei Kapishnikov ,  Fernanda Bertini Viégas ,  Michael Andrew Terry ,  Tolga Bolukbasi

IPC: G06N20/00 ,  G06N5/04 ,  G06N20/10

CPC classification number: G06N20/00 ,  G06N5/04 ,  G06N20/10

Abstract: Methods, systems, devices, and tangible non-transitory computer readable media for saliency visualization are provided. The disclosed technology can include receiving a data input including a plurality of features. The data input can be segmented into regions. At least one of the regions can include two or more of the features. Attribution scores can be respectively generated for features of the data input. The attribution scores for each feature can be indicative of a respective saliency of such feature. A respective gain value for each region can be determined over one or more iterations based on the respective attribution scores associated with the features included in the region. Further, at each iteration one or more of the regions with the greatest gain values can be added to a saliency mask. Furthermore, at each iteration a saliency visualization can be produced based on the saliency mask.

公开(公告)号：US20210192382A1

公开(公告)日：2021-06-24

申请号：US16719244

申请日：2019-12-18

Applicant: Google LLC

Inventor： Andrei Kapishnikov ,  Tolga Bolukbasi ,  Fernanda Bertini Viégas ,  Michael Andrew Terry

IPC: G06N20/00 ,  G06N5/04

Abstract: Methods, systems, devices, and tangible non-transitory computer readable media for saliency visualization are provided. The disclosed technology can include receiving a data input including a plurality of features. The data input can be segmented into regions. At least one of the regions can include two or more of the features. Attribution scores can be respectively generated for features of the data input. The attribution scores for each feature can be indicative of a respective saliency of such feature. A respective gain value for each region can be determined over one or more iterations based on the respective attribution scores associated with the features included in the region. Further, at each iteration one or more of the regions with the greatest gain values can be added to a saliency mask. Furthermore, at each iteration a saliency visualization can be produced based on the saliency mask.

公开(公告)号：US20240037145A1

公开(公告)日：2024-02-01

申请号：US17878845

申请日：2022-08-01

Applicant: Google LLC

Inventor： Marco Ziccardi ,  Min-hsuan Tsai ,  Wei-Hong Chuang ,  Rahul Sunil Bhalerao ,  Ye Xia ,  Madhuri Shanbhogue ,  Mojtaba Seyedhosseini ,  Mike Krainin ,  Andrei Kapishnikov ,  Yuanzhen Li

IPC: G06F16/783 ,  G06F16/78 ,  G06F40/56

CPC classification number: G06F16/7837 ,  G06F16/7867 ,  G06F40/56

Abstract: A method includes obtaining first data including a first identifier of a first product determine in association with a content item based on first metadata of the content item. The method further includes obtaining a first confidence value associated with the first product and the content item. The method further includes obtaining second data including a second identifier of the first product and a second confidence value. The method further includes providing the first data and the second data to a trained machine learning model. The method further includes obtaining a third confidence value from the trained machine learning model associated with the first product. The method further includes adjusting second metadata of the content item in view of the third confidence value.