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公开(公告)号：US20170357877A1
公开(公告)日：2017-12-14
申请号：US15177197
申请日：2016-06-08
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Yufei Wang , Radomir Mech , Xiaohui Shen , Gavin Stuart Peter Miller
CPC classification number: G06K9/6218 , G06F17/30247 , G06F17/30265 , G06F17/3028 , G06K9/00228 , G06K9/00677 , G06K9/00718 , G06K9/00751 , G06K9/4628 , G06K9/6215 , G06K9/6254 , G06K9/6255 , G06K9/628 , G06N3/0454 , G06N3/084
Abstract: In embodiments of event image curation, a computing device includes memory that stores a collection of digital images associated with a type of event, such as a digital photo album of digital photos associated with the event, or a video of image frames and the video is associated with the event. A curation application implements a convolutional neural network, which receives the digital images and a designation of the type of event. The convolutional neural network can then determine an importance rating of each digital image within the collection of the digital images based on the type of the event. The importance rating of a digital image is representative of an importance of the digital image to a person in context of the type of the event. The convolutional neural network generates an output of representative digital images from the collection based on the importance rating of each digital image.
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公开(公告)号：US09940544B2
公开(公告)日：2018-04-10
申请号：US15177197
申请日：2016-06-08
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Yufei Wang , Radomir Mech , Xiaohui Shen , Gavin Stuart Peter Miller
CPC classification number: G06K9/6218 , G06F17/30247 , G06F17/30265 , G06F17/3028 , G06K9/00228 , G06K9/00677 , G06K9/00718 , G06K9/00751 , G06K9/4628 , G06K9/6215 , G06K9/6254 , G06K9/6255 , G06K9/628 , G06N3/0454 , G06N3/084
Abstract: In embodiments of event image curation, a computing device includes memory that stores a collection of digital images associated with a type of event, such as a digital photo album of digital photos associated with the event, or a video of image frames and the video is associated with the event. A curation application implements a convolutional neural network, which receives the digital images and a designation of the type of event. The convolutional neural network can then determine an importance rating of each digital image within the collection of the digital images based on the type of the event. The importance rating of a digital image is representative of an importance of the digital image to a person in context of the type of the event. The convolutional neural network generates an output of representative digital images from the collection based on the importance rating of each digital image.
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公开(公告)号：US20180211135A1
公开(公告)日：2018-07-26
申请号：US15935816
申请日：2018-03-26
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Yufei Wang , Radomir Mech , Xiaohui Shen , Gavin Stuart Peter Miller
CPC classification number: G06K9/6218 , G06F16/51 , G06F16/58 , G06F16/583 , G06K9/00228 , G06K9/00677 , G06K9/00718 , G06K9/00751 , G06K9/4628 , G06K9/6215 , G06K9/6254 , G06K9/6255 , G06K9/628 , G06N3/0454 , G06N3/084
Abstract: In embodiments of event image curation, a computing device includes memory that stores a collection of digital images associated with a type of event, such as a digital photo album of digital photos associated with the event, or a video of image frames and the video is associated with the event. A curation application implements a convolutional neural network, which receives the digital images and a designation of the type of event. The convolutional neural network can then determine an importance rating of each digital image within the collection of the digital images based on the type of the event. The importance rating of a digital image is representative of an importance of the digital image to a person in context of the type of the event. The convolutional neural network generates an output of representative digital images from the collection based on the importance rating of each digital image.
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公开(公告)号：US20170357892A1
公开(公告)日：2017-12-14
申请号：US15177121
申请日：2016-06-08
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Yufei Wang , Radomir Mech , Xiaohui Shen , Gavin Stuart Peter Miller
Abstract: In embodiments of convolutional neural network joint training, a computing system memory maintains different data batches of multiple digital image items, where the digital image items of the different data batches have some common features. A convolutional neural network (CNN) receives input of the digital image items of the different data batches, and classifier layers of the CNN are trained to recognize the common features in the digital image items of the different data batches. The recognized common features are input to fully-connected layers of the CNN that distinguish between the recognized common features of the digital image items of the different data batches. A scoring difference is determined between item pairs of the digital image items in a particular one of the different data batches. A piecewise ranking loss algorithm maintains the scoring difference between the item pairs, and the scoring difference is used to train CNN regression functions.
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