公开(公告)号：US10956793B1

公开(公告)日：2021-03-23

申请号：US16192419

申请日：2018-11-15

Applicant: Snap Inc.

Inventor： Xiaoyu Wang ,  Ning Xu ,  Ning Zhang ,  Vitor R. Carvalho ,  Jia Li

IPC: G06K9/62 ,  G06N3/08 ,  G06T1/00 ,  G06F16/58

Abstract: Systems, methods, devices, media, and computer readable instructions are described for local image tagging in a resource constrained environment. One embodiment involves processing image data using a deep convolutional neural network (DCNN) comprising at least a first subgraph and a second subgraph, the first subgraph comprising at least a first layer and a second layer, processing, the image data using at least the first layer of the first subgraph to generate first intermediate output data; processing, by the mobile device, the first intermediate output data using at least the second layer of the first subgraph to generate first subgraph output data, and in response to a determination that each layer reliant on the first intermediate data have completed processing, deleting the first intermediate data from the mobile device. Additional embodiments involve convolving entire pixel resolutions of the image data against kernels in different layers if the DCNN.

公开(公告)号：US11822600B2

公开(公告)日：2023-11-21

申请号：US17248386

申请日：2021-01-22

Applicant: Snap Inc.

Inventor： Xiaoyu Wang ,  Ning Xu ,  Ning Zhang ,  Vitor R. Carvalho ,  Jia Li

IPC: G06F16/58 ,  G06T1/00 ,  G06N3/08 ,  G06F16/9038 ,  G06N3/04 ,  G06F18/24 ,  G06N3/045 ,  H04N23/63 ,  G06V10/764 ,  G06V10/82 ,  G06V10/75 ,  G06N5/022

CPC classification number: G06F16/5866 ,  G06F16/9038 ,  G06F18/24 ,  G06N3/04 ,  G06N3/045 ,  G06N3/08 ,  G06T1/0007 ,  G06V10/751 ,  G06V10/764 ,  G06V10/82 ,  H04N23/63 ,  G06N5/022 ,  G06V2201/09

Abstract: Systems, methods, devices, media, and computer readable instructions are described for local image tagging in a resource constrained environment. One embodiment involves processing image data using a deep convolutional neural network (DCNN) comprising at least a first subgraph and a second subgraph, the first subgraph comprising at least a first layer and a second layer, processing, the image data using at least the first layer of the first subgraph to generate first intermediate output data; processing, by the mobile device, the first intermediate output data using at least the second layer of the first subgraph to generate first subgraph output data, and in response to a determination that each layer reliant on the first intermediate data have completed processing, deleting the first intermediate data from the mobile device. Additional embodiments involve convolving entire pixel resolutions of the image data against kernels in different layers if the DCNN.

公开(公告)号：US10157333B1

公开(公告)日：2018-12-18

申请号：US15247697

申请日：2016-08-25

Applicant: Snap Inc.

Inventor： Xiaoyu Wang ,  Ning Xu ,  Ning Zhang ,  Vitor R. Carvalho ,  Jia Li

IPC: G06K9/62 ,  G06T1/00 ,  G06N3/08 ,  G06F17/30

Abstract: Systems, methods, devices, media, and computer readable instructions are described for local image tagging in a resource constrained environment. One embodiment involves processing image data using a deep convolutional neural network (DCNN) comprising at least a first subgraph and a second subgraph, the first subgraph comprising at least a first layer and a second layer, processing, the image data using at least the first layer of the first subgraph to generate first intermediate output data; processing, by the mobile device, the first intermediate output data using at least the second layer of the first subgraph to generate first subgraph output data, and in response to a determination that each layer reliant on the first intermediate data have completed processing, deleting the first intermediate data from the mobile device. Additional embodiments involve convolving entire pixel resolutions of the image data against kernels in different layers if the DCNN.