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公开(公告)号:US20190138898A1
公开(公告)日:2019-05-09
申请号:US16107717
申请日:2018-08-21
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Joonho SONG , Sehwan LEE , Junwoo JANG
Abstract: A neural network apparatus configured to perform a deconvolution operation includes a memory configured to store a first kernel; and a processor configured to: obtain, from the memory, the first kernel; calculate a second kernel by adjusting an arrangement of matrix elements comprised in the first kernel; generate sub-kernels by dividing the second kernel; perform a convolution operation between an input feature map and the sub-kernels using a convolution operator; and generate an output feature map, as a deconvolution of the input feature map, by merging results of the convolution operation.
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12.
公开(公告)号:US20230186050A1
公开(公告)日:2023-06-15
申请号:US18107210
申请日:2023-02-08
Applicant: Samsung Electronics Co., Ltd.
Inventor: Saptarsi DAS , Sabitha KUSUMA , Sehwan LEE , Ankur DESHWAL , Kiran Kolar CHANDRASEKHARAN
Abstract: A method and an apparatus for processing layers in a neural network fetch Input Feature Map (IFM) tiles of an IFM tensor and kernel tiles of a kernel tensor, perform a convolutional operation on the IFM tiles and the kernel tiles by exploiting IFM sparsity and kernel sparsity, and generate a plurality of OFM tiles corresponding to the IFM tiles.
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13.
公开(公告)号:US20220374651A1
公开(公告)日:2022-11-24
申请号:US17851704
申请日:2022-06-28
Applicant: Samsung Electronics Co., Ltd.
Inventor: DINESH KUMAR YADAV , ANKUR DESHWAL , SAPTARSI DAS , Junwoo JANG , Sehwan LEE
Abstract: A method of performing convolution in a neural network with variable dilation rate is provided. The method includes receiving a size of a first kernel and a dilation rate, determining at least one of size of one or more disintegrated kernels based on the size of the first kernel, a baseline architecture of a memory and the dilation rate, determining an address of one or more blocks of an input image based on the dilation rate, and one or more parameters associated with a size of the input image and the memory. Thereafter, the one or more blocks of the input image and the one or more disintegrated kernels are fetched from the memory, and an output image is obtained based on convolution of each of the one or more disintegrated kernels and the one or more blocks of the input image.
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公开(公告)号:US20220284262A1
公开(公告)日:2022-09-08
申请号:US17368470
申请日:2021-07-06
Applicant: SAMSUNG ELECTRONICS CO., LTD. , UNIST(ULSAN NATIONAL INSTITUTE OF SCIENCE AND TECHNOLOGY)
Inventor: Sehwan LEE , Hyeonuk SIM , Jongeun LEE
IPC: G06N3/04
Abstract: A neural network operation apparatus and method implementing quantization is disclosed. The neural network operation method may include receiving a weight of a neural network, a candidate set of quantization points, and a bitwidth for representing the weight, extracting a subset of quantization points from the candidate set of quantization points based on the bitwidth, calculating a quantization loss based on the weight of the neural network and the subset of quantization points, and generating a target subset of quantization points based on the quantization loss.
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公开(公告)号:US20210064992A1
公开(公告)日:2021-03-04
申请号:US16803342
申请日:2020-02-27
Applicant: Samsung Electronics Co., Ltd.
Inventor: Hyunsun PARK , Yoojin KIM , Hyeongseok YU , Sehwan LEE , Junwoo JANG
Abstract: A method of processing data includes identifying a sparsity of input data, based on valid information included in the input data, rearranging the input data, based on a form of the sparsity, and generating output data by processing the rearranged input data.
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公开(公告)号:US20200210806A1
公开(公告)日:2020-07-02
申请号:US16558493
申请日:2019-09-03
Applicant: Samsung Electronics Co., Ltd.
Inventor: Sehwan LEE
Abstract: Provided are a method of performing a convolution operation between a kernel and an input feature map based on reuse of the input feature map, and a neural network apparatus using the method. The neural network apparatus generates output values of an operation between each of weights of a kernel and an input feature map, and generates an output feature map by accumulating the output values at positions in the output feature map that are set based on positions of the weights in the kernel.
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公开(公告)号:US20190340504A1
公开(公告)日:2019-11-07
申请号:US16244644
申请日:2019-01-10
Applicant: Samsung Electronics Co., Ltd.
Inventor: Junhaeng LEE , Hyunsun PARK , Sehwan LEE , Seungwon LEE
IPC: G06N3/08
Abstract: A neural network method and apparatus is provided. A processor-implemented neural network method includes determining, based on a determined number of classes of input data, a precision for a neural network layer outputting an operation result, and processing parameters of the layer according to the determined precision.
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公开(公告)号:US20190130250A1
公开(公告)日:2019-05-02
申请号:US16168418
申请日:2018-10-23
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Hyunsun PARK , Wonjo LEE , Sehwan LEE , Seungwon LEE
Abstract: A process-implemented neural network method includes obtaining a plurality of kernels and an input feature map; determining a pruning index indicating a weight location where pruning is to be performed commonly within the plurality of kernels; and performing a Winograd-based convolution operation by pruning a weight corresponding to the determined pruning index with respect to each of the plurality of kernels.
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公开(公告)号:US20190065896A1
公开(公告)日:2019-02-28
申请号:US16110664
申请日:2018-08-23
Inventor: Sehwan LEE , Leesup KIM , Hyeonuk KIM , Jaehyeong SIM , Yeongjae CHOI
CPC classification number: G06K9/623 , G06K9/6251 , G06K9/6267 , G06N3/04 , G06N3/0454 , G06N3/063
Abstract: A processor-implemented neural network method includes: obtaining, from a memory, data an input feature map and kernels having a binary-weight, wherein the kernels are to be processed in a layer of a neural network; decomposing each of the kernels into a first type sub-kernel reconstructed with weights of a same sign, and a second type sub-kernel for correcting a difference between a respective kernel, among the kernels, and the first type sub-kernel; performing a convolution operation by using the input feature map and the first type sub-kernels and the second type sub-kernels decomposed from each of the kernels; and obtaining an output feature map by combining results of the convolution operation.
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20.
公开(公告)号:US20240362471A1
公开(公告)日:2024-10-31
申请号:US18764864
申请日:2024-07-05
Applicant: Samsung Electronics Co., Ltd.
Inventor: Sehwan LEE , Namjoon KIM , Joonho SONG , Junwoo JANG
Abstract: Provided are a method and apparatus for processing a convolution operation in a neural network, the method includes determining a precision of feature map operands and a precision of weight operands, respectively, on which the convolution operation is to be performed in parallel, decomposing a multiplier included in a convolution operator into sub-multipliers based on the precision of the feature map operands and the precision of the weight operands, performing the convolution operation between the feature map operands and the weight operands by using the decomposed sub-multipliers, each operand being processed in a sub-multiplier corresponding to a precision of the operand, and obtaining output feature maps corresponding to results of the convolution operation.
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