公开(公告)号：US20240112456A1

公开(公告)日：2024-04-04

申请号：US18538723

申请日：2023-12-13

Applicant: SAMSUNG ELECTRONICS CO, LTD.

Inventor： Sarvesh . ,  Kinsuk DAS ,  Raj Narayana GADDE

IPC: G06V10/82 ,  G06T3/40 ,  G06V10/771

CPC classification number: G06V10/82 ,  G06T3/40 ,  G06V10/771

Abstract: A method for optimizing multi-frame processing model of a neural network includes: receiving a plurality of input frames by a processing engine that is configured to execute a multi frame processing model, the multi frame processing model including a plurality of convolution layers; selecting a pre-determined number of frames from the received plurality of frames for processing by the plurality of convolution layers; determining, as a sequence of frames, at least a preceding frame and a plurality of following frames amongst the selected pre-determined number of frames; removing the preceding frame by processing the sequence of frames using a plurality of filters in the multi frame processing model; and concatenating the plurality of following frames in an order, to the plurality of input frames for subsequent receiving by the multi frame processing model.

公开(公告)号：US20230004778A1

公开(公告)日：2023-01-05

申请号：US17857731

申请日：2022-07-05

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Sai Karthikey PENTAPATI ,  Amit SHUKLA ,  Kinsuk DAS ,  Raj Narayana GADDE ,  Sandeep MISHRA ,  Sarvesh ,  Sandeep PALAKKAL

IPC: G06N3/04 ,  G06K9/62 ,  G06F7/76

Abstract: The disclosure relates to method and system for on-device inference in a deep neural network (DNN). The method comprises: determining whether one or more layers of the DNN satisfy one of a first, a second and a third condition, the one or more layers including one or more convolution layers and one or more resampling layers; performing the on-device inference based on the determination, wherein performing the on-device inference comprises at least one of: optimizing the one or more convolution layers in the one or more parallel branches based on the one or more layers of the DNN satisfying the first condition, optimizing the at least one of the resampling layers based on the one or more layers of the DNN satisfying the second condition, and modifying operation of the at least one of the resampling layers based on the one or more layers of the DNN satisfying the third condition.

公开(公告)号：US20220385914A1

公开(公告)日：2022-12-01

申请号：US17868421

申请日：2022-07-19

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Sirish Kumar PASUPULETI ,  Raj Narayana GADDE ,  Sarvesh ,  Kinsuk DAS ,  Ankit SINGH ,  Sai Harish AVULA

IPC: H04N19/132 ,  H04N19/30 ,  H04N19/86 ,  H04N19/172

Abstract: The present disclosure refers to methods and apparatuses for processing of high-resolution video content. In an embodiment, a method includes generating a first group of video frames from the video content. The first group of video frames has a first resolution lower than a resolution of the video content and a first rate-distortion score. The method further includes generating a second group of video frames from the video content. The second group of video frames has a second resolution lower than the resolution of the video content and a second rate-distortion score. The method further includes selecting an optimal group of video frames from the first and second groups of video frames based on a comparison between the first and second rate-distortion scores. The optimal group of video frames has a rate-distortion score lower than the first and the second rate-distortion scores.