公开(公告)号：US11456007B2

公开(公告)日：2022-09-27

申请号：US16451969

申请日：2019-06-25

Applicant: Samsung Electronics Co., Ltd.

Inventor： Jaeyoung Kim ,  Mostafa El-Khamy ,  Jungwon Lee

IPC: G10L25/30 ,  G10L21/02 ,  G10L25/60 ,  G10L21/0208 ,  G10L15/06

Abstract: A method and system for providing end-to-end multi-task denoising for joint signal distortion ratio (SDR) and perceptual evaluation of speech quality (PESQ) optimization is herein disclosed. According to one embodiment, an method includes receiving a noisy signal, generating a denoised output signal, determining a signal distortion ratio (SDR) loss function based on the denoised output signal, determining a perceptual evaluation of speech quality (PESQ) loss function based on the denoised output signal, and optimizing an overall loss function based on the PESQ loss function and the SDR loss function.

公开(公告)号：US11354577B2

公开(公告)日：2022-06-07

申请号：US16138279

申请日：2018-09-21

Applicant: Samsung Electronics Co., Ltd.

Inventor： Haoyu Ren ,  Mostafa El-Khamy ,  Jungwon Lee

IPC: G06N3/08 ,  G06T5/00 ,  G06T3/40 ,  G06N3/04 ,  G06T7/13

Abstract: Apparatuses and methods of manufacturing same, systems, and methods are described. In one aspect, a method includes generating a convolutional neural network (CNN) by training a CNN having three or more convolutional layers, and performing cascade training on the trained CNN. The cascade training includes an iterative process of one or more stages, in which each stage includes inserting a residual block (ResBlock) including at least two additional convolutional layers and training the CNN with the inserted ResBlock.

公开(公告)号：US11164071B2

公开(公告)日：2021-11-02

申请号：US15634537

申请日：2017-06-27

Applicant: Samsung Electronics Co., Ltd.

Inventor： Mostafa El-Khamy ,  Yoo Jin Choi ,  Jungwon Lee

IPC: G06N3/06 ,  G06N3/08 ,  G06N3/04 ,  G06F5/01 ,  G06F17/16

Abstract: Disclosed herein is convolutional neural network (CNN) system for generating a classification for an input image. According to an embodiment, the CNN system comprises a sequence of neural network layers configured to: derive a feature map based on at least the input image; puncture at least one selection among the feature map and a kernel by setting the value of one or more elements of a row of the at least one selection to zero according to a pattern and cyclic shifting the pattern by a predetermined interval per row to set the value of one or more elements of the rest of the rows of the at least one selection according to the cyclic shifted pattern; convolve the feature map with the kernel to generate a first convolved output; and generate the classification for the input image based on at least the first convolved output.

公开(公告)号：US20210319326A1

公开(公告)日：2021-10-14

申请号：US16886429

申请日：2020-05-28

Applicant: Samsung Electronics Co., Ltd.

Inventor： Yoo Jin Choi ,  Jongha Ryu ,  Mostafa El-Khamy ,  Jungwon Lee ,  Young-Han Kim

IPC: G06N3/08 ,  G06N3/04

Abstract: A system and method for operating a neural network. In some embodiments, the neural network includes a variational autoencoder, and the training of the neural network includes training the variational autoencoder with a plurality of samples of a first random variable; and a plurality of samples of a second random variable, the plurality of samples of the first random variable and the plurality of samples of the second random variable being unpaired, the training of the neural network including updating weights in the neural network based on a first loss function, the first loss function being based on a measure of deviation from consistency between: a conditional generation path from the first random variable to the second random variable, and a conditional generation path from the second random variable to the first random variable.

公开(公告)号：US20210224953A1

公开(公告)日：2021-07-22

申请号：US17223991

申请日：2021-04-06

Applicant: Samsung Electronics Co., Ltd.

Inventor： Mostafa El-Khamy ,  Jungwon Lee ,  Haoyu Ren

IPC: G06T3/40 ,  G06N3/04 ,  G06N3/08

Abstract: In a method for super resolution imaging, the method includes: receiving, by a processor, a low resolution image; generating, by the processor, an intermediate high resolution image having an improved resolution compared to the low resolution image; generating, by the processor, a final high resolution image based on the intermediate high resolution image and the low resolution image; and transmitting, by the processor, the final high resolution image to a display device for display thereby.

公开(公告)号：US10862630B2

公开(公告)日：2020-12-08

申请号：US14847320

申请日：2015-09-08

Applicant: Samsung Electronics Co., Ltd.

Inventor： Mostafa El-Khamy ,  Arvind Yedla ,  SangHyuck Ha ,  Hyunsang Cho ,  Inyup Kang

IPC: H04L1/18 ,  H04L5/00

Abstract: Apparatuses (including user equipment (UE) and modem chips for UEs), systems, and methods for UE downlink Hybrid Automatic Repeat reQuest (HARQ) buffer memory management are described. In one method, the entire UE DL HARQ buffer memory space is pre-partitioned according to the number and capacities of the UE's active carrier components. In another method, the UE DL HARQ buffer is split between on-chip and off-chip memory so that each partition and sub-partition is allocated between the on-chip and off-chip memories in accordance with an optimum ratio.

公开(公告)号：US10803378B2

公开(公告)日：2020-10-13

申请号：US15655557

申请日：2017-07-20

Applicant: Samsung Electronics Co., Ltd.

Inventor： Haoyu Ren ,  Mostafa El-Khamy ,  Jungwon Lee

IPC: G06N3/04 ,  G06N3/08

Abstract: Apparatuses and methods of manufacturing same, systems, and methods for generating a convolutional neural network (CNN) are described. In one aspect, a minimal CNN having, e.g., three or more layers is trained. Cascade training may be performed on the trained CNN to insert one or more intermediate layers until a training error is less than a threshold. When cascade training is complete, cascade network trimming of the CNN output from the cascade training may be performed to improve computational efficiency. To further reduce network parameters, convolutional filters may be replaced with dilated convolutional filters with the same receptive field, followed by additional training/fine-tuning.

公开(公告)号：US20200312346A1

公开(公告)日：2020-10-01

申请号：US16751094

申请日：2020-01-23

Applicant: Samsung Electronics Co., Ltd.

Inventor： Amin Fazeli ,  Mostafa El-Khamy ,  Jungwon Lee

IPC: G10L21/0232 ,  G06N3/08 ,  H04R3/04 ,  G06N20/10

Abstract: A system for performing echo cancellation includes: a processor configured to: receive a far-end signal; record a microphone signal including: a near-end signal; and an echo signal corresponding to the far-end signal; extract far-end features from the far-end signal; extract microphone features from the microphone signal; compute estimated near-end features by supplying the microphone features and the far-end features to an acoustic echo cancellation module including a recurrent neural network including: an encoder including a plurality of gated recurrent units; and a decoder including a plurality of gated recurrent units; compute an estimated near-end signal from the estimated near-end features; and transmit the estimated near-end signal to the far-end device. The recurrent neural network may include a contextual attention module; and the recurrent neural network may take, as input, a plurality of error features computed based on the far-end features, the microphone features, and acoustic path parameters.

公开(公告)号：US20190095795A1

公开(公告)日：2019-03-28

申请号：US16138279

申请日：2018-09-21

Applicant: Samsung Electronics Co., Ltd.

Inventor： Haoyu Ren ,  Mostafa El-Khamy ,  Jungwon Lee

IPC: G06N3/08 ,  G06T5/00

Abstract: Apparatuses and methods of manufacturing same, systems, and methods are described. In one aspect, a method includes generating a convolutional neural network (CNN) by training a CNN having three or more convolutional layers, and performing cascade training on the trained CNN. The cascade training includes an iterative process of one or more stages, in which each stage includes inserting a residual block (ResBlock) including at least two additional convolutional layers and training the CNN with the inserted ResBlock.

公开(公告)号：US10153787B2

公开(公告)日：2018-12-11

申请号：US15398378

申请日：2017-01-04

Applicant: Samsung Electronics Co., Ltd.

Inventor： Mostafa El-Khamy ,  Hsien-Ping Lin ,  Jungwon Lee

IPC: H03M13/00 ,  H03M13/39 ,  G06F17/50 ,  H01L21/66 ,  H03M13/13 ,  H04L1/00

Abstract: An apparatus and a method. The apparatus includes a receiver to receive a polar codeword of length mj; a processor configured to determine a decoding node tree structure with mj leaf nodes for the received codeword, and receive i indicating a level at which parallelism of order m is applied to the decoding node tree structure, wherein i indicates levels of the decoding node tree structure, and wherein the mj leaf nodes are at level j; and m successive cancellation list decoders (SCLDs) applied to each child node of each node in the decoding node tree structure at level i−1, wherein each of the m SCLDs executes in parallel to determine log likelihood ratios (LLRs) for a codeword of length mj-i, and wherein each of the m SCLDs uses LLRs of an associated parent node without using a hard decision or a soft reliability estimate of any other node of the other m SCLDs.