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公开(公告)号:US20230252602A1
公开(公告)日:2023-08-10
申请号:US17978458
申请日:2022-11-01
Applicant: SAMSUNG ELECTRONICS CO, LTD.
IPC: G06T3/40
CPC classification number: G06T3/4046
Abstract: Embodiments of the disclosure provide a method and device for efficiently reducing dimensions of an image frame by an electronic device. The method includes: receiving the image frame; transforming the image frame from a spatial domain comprising a first plurality of channels to a non-spatial domain comprising a second plurality of channels, where a number of the second plurality of channels is greater than a number of the first plurality of channels; removing channels comprising irrelevant information from among the second plurality of channels using an AI engine to generate a low-resolution image frame in the non-spatial domain; and providing the low-resolution image frame to a neural network for a faster and accurate inference of the image frame.
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公开(公告)号:US20230068381A1
公开(公告)日:2023-03-02
申请号:US17961453
申请日:2022-10-06
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Tejpratap Venkata Subbu Lakshmi GOLLANAPALLI , Arun ABRAHAM , Raja KUMAR , Pradeep NELAHONNE SHIVAMURTHAPPA , Vikram Nelvoy RAJENDIRAN , Prasen Kumar SHARMA
Abstract: Various embodiments of the disclosure disclose a method for quantizing a Deep Neural Network (DNN) model in an electronic device. The method includes: estimating, by the electronic device, an activation range of each layer of the DNN model using self-generated data (e.g. retro image, audio, video, etc.) and/or a sensitive index of each layer of the DNN model; quantizing, by the electronic device, the DNN model based on the activation range and/or the sensitive index; and allocating, by the electronic device, a dynamic bit precision for each channel of each layer of the DNN model to quantize the DNN model.
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