公开(公告)号：US20240069875A1

公开(公告)日：2024-02-29

申请号：US18209617

申请日：2023-06-14

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Jae-Bok PARK ,  Chang-Sik CHO ,  Kyung-Hee LEE ,  Ji-Young KWAK ,  Seon-Tae KIM ,  Hong-Soog KIM ,  Jin-Wuk SEOK ,  Hyun-Woo CHO

IPC: G06F8/36 ,  G06F8/60 ,  G06F9/451

CPC classification number: G06F8/36 ,  G06F8/60 ,  G06F9/453

Abstract: Disclosed herein are a neural network model deployment method and apparatus for providing a deep learning service. The neural network model deployment method may include providing a specification wizard to a user, searching for and training a neural network based on a user requirement specification that is input through the specification wizard, generating a neural network template code based on the user requirement specification and the trained neural network, converting the trained neural network into a deployment neural network that is usable in a target device based on the user requirement specification, and deploying the deployment neural network to the target device.

公开(公告)号：US20230316091A1

公开(公告)日：2023-10-05

申请号：US18166948

申请日：2023-02-09

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Jin-Wuk SEOK ,  Ji-Young KWAK ,  Seon-Tae KIM ,  Hong-Soog KIM ,  Jae-Bok PARK ,  Kyung-Hee LEE ,  Chang-Sik CHO ,  Hyun-Woo CHO

IPC: G06N3/098

CPC classification number: G06N3/098

Abstract: Disclosed herein are a federated learning method and apparatus. The federated learning method includes receiving a feature vector extracted from a client side and label data corresponding to the feature vector, outputting a feature vector with phase information preserved therein by applying the feature vector as input of a Self-Organizing Feature Map (SOFM), and training a neural network model by applying both the feature vector with the phase information preserved therein and the label data as input of a neural network model.

公开(公告)号：US20220300803A1

公开(公告)日：2022-09-22

申请号：US17342354

申请日：2021-06-08

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Hyun-Woo CHO ,  Jeong-Si KIM ,  Hong-Soog KIM ,  Jin-Wuk SEOK ,  Seung-Tae HONG

IPC: G06N3/08 ,  G06N3/04

Abstract: Disclosed herein are a method for performing a dilated convolution operation using an atypical kernel pattern and a dilated convolutional neural network system using the same. The method for performing a dilated convolution operation includes learning a weight matrix for a kernel of dilated convolution through deep learning, generating an atypical kernel pattern based on the learned weight matrix, and performing a dilated convolution operation on input data by applying the atypical kernel pattern to a kernel of a dilated convolutional neural network.