公开(公告)号：US20230274479A1

公开(公告)日：2023-08-31

申请号：US18027326

申请日：2021-09-29

Applicant: RESEARCH COOPERATION FOUNDATION OF YEUNGNAM UNIVERSITY

Inventor： Gyu Sang CHOI ,  Jong Ho HAN ,  Hyun Kwang SHIN

IPC: G06T11/60 ,  G06F40/30 ,  G06T5/50

CPC classification number: G06T11/60 ,  G06F40/30 ,  G06T5/50 ,  G06T2207/20081

Abstract: A learning apparatus for image generation includes a preprocessing module configured to receive text for image generation and generate a sentence feature vector and a word feature vector from the received text, a first generative adversarial network (GAN) configured to receive the sentence feature vector from the preprocessing module and generate an initial image based on the received sentence feature vector, and a second generative adversarial network configured to receive the word feature vector generated by the preprocessing module and the initial image generated by the first generative adversarial network and generate a final image based on the word feature vector and the initial image.

公开(公告)号：US20210406554A1

公开(公告)日：2021-12-30

申请号：US17084877

申请日：2020-10-30

Applicant: RESEARCH COOPERATION FOUNDATION OF YEUNGNAM UNIVERSITY

Inventor： Gyu Sang CHOI ,  Jong Ho HAN ,  Hyun Kwang SHIN

IPC: G06K9/00 ,  G06K9/62 ,  G06N3/04 ,  G06N3/08

Abstract: A learning apparatus for creating an emotion expression video according to an embodiment disclosed include first generative adversarial networks (GAN) that receive text for creating an emotion expression video, extract vector information by performing embedding on the input text, and create an image based on the extracted vector information, and second generative adversarial networks that receive an emotion expression image and a frame of comparison video, and create a frame of emotion expression video from the emotion expression image and the frame of comparison video.

公开(公告)号：US20240095913A1

公开(公告)日：2024-03-21

申请号：US18373677

申请日：2023-09-27

Applicant: RESEARCH COOPERATION FOUNDATION OF YEUNGNAM UNIVERSITY

Inventor： Gyu Sang CHOI ,  Kyeong Min PARK ,  Min Cheol CHANG

IPC: G06T7/00 ,  G06T3/40 ,  G06V10/24 ,  G06V10/42 ,  G06V10/74

CPC classification number: G06T7/0012 ,  G06T3/40 ,  G06V10/242 ,  G06V10/42 ,  G06V10/761 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/20084 ,  G06T2207/30016

Abstract: An apparatus for image transformation for transforming a first medical image into a second medical image based on an artificial neural network technology includes a preprocessing module that receives the first medical image and second medical image obtained by photographing the same part of a body using different photographing techniques and performs preprocessing on the first and second medical images, and an artificial neural network module that receives the preprocessed first medical image and second medical image, respectively, and transforms the first medical image into a second medical image.

公开(公告)号：US20230005152A1

公开(公告)日：2023-01-05

申请号：US17723767

申请日：2022-04-19

Applicant: RESEARCH COOPERATION FOUNDATION OF YEUNGNAM UNIVERSITY

Inventor： Gyu Sang CHOI ,  Hyun Kwang SHIN

IPC: G06T7/10 ,  G06N3/04

Abstract: An apparatus for image segmentation according to an embodiment includes an acquirer configured to acquire one or more images in which an object is photographed and a segmentation performer configured to perform segmentation on the one or more images using a segmentation model which is deep learned through a plurality of images, in which the segmentation model is a U-Net-based model including a first type module based on depth-wise separable convolution (DSC) and a second type module based on global context network (GCNet).

公开(公告)号：US20200334010A1

公开(公告)日：2020-10-22

申请号：US16851350

申请日：2020-04-17

Applicant: RESEARCH COOPERATION FOUNDATION OF YEUNGNAM UNIVERSITY

Inventor： Gyu Sang CHOI

IPC: G06F7/08

Abstract: A method of data alignment according to an embodiment of the present invention is performed by a computing device including one or more processors and a memory in which one or more programs to be executed by the one or more processors are stored, and the method includes counting the number of target data to be aligned, calculating a distribution of the target data, determining the number of bits of a bucket and the number of slots of the bucket for aligning the target data on the basis of the number of target data and the distribution of the target data, and generating buckets corresponding to the determined numbers of bits and slots and allocating the target data to the buckets to align the target data.