Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Hyemin Ahn"'
Autor:
Se Jin Choi, Kyung Won Kim, Yousun Ko, Young Chul Cho, Ji Sung Jang, Hyemin Ahn, Dong Wook Kim, Mi Young Kim
Publikováno v:
Diagnostics, Vol 14, Iss 6, p 583 (2024)
Background: To use the apparent diffusion coefficient (ADC) as reliable biomarkers, validation of MRI equipment performance and clinical acquisition protocols should be performed prior to application in patients. This study aims to validate various M
Externí odkaz:
https://doaj.org/article/e172a56039ae4d59b1aae3f114c46f72
Autor:
Sun Yeop Lee, Sangwoo Ha, Min Gyeong Jeon, Hao Li, Hyunju Choi, Hwa Pyung Kim, Ye Ra Choi, Hoseok I, Yeon Joo Jeong, Yoon Ha Park, Hyemin Ahn, Sang Hyup Hong, Hyun Jung Koo, Choong Wook Lee, Min Jae Kim, Yeon Joo Kim, Kyung Won Kim, Jong Mun Choi
Publikováno v:
npj Digital Medicine, Vol 5, Iss 1, Pp 1-11 (2022)
Abstract While many deep-learning-based computer-aided detection systems (CAD) have been developed and commercialized for abnormality detection in chest radiographs (CXR), their ability to localize a target abnormality is rarely reported. Localizatio
Externí odkaz:
https://doaj.org/article/ff3c6c9a53e747358a67d27c466ca813
Autor:
Cheng Shi Chen1, Hyemin Ahn2, Ji Hoon Shin1 jhshin@amc.seoul.kr, Hai-Liang Li1, Jong Woo Kim2, Ibrahim, Alrashidi2, Hee Ho Chu2
Publikováno v:
Pakistan Journal of Medical Sciences. Jul/Aug2021, Vol. 37 Issue 4, p1111-1117. 7p.
Autor:
HYEMIN AHN, MIN HEE LEE, SEUNG HEE BYUN, HWA JUNG KIM, WANLIM KIM, CHOONG GEUN CHEE, HYE WON CHUNG, MIN A YOON, SANG HOON LEE
Publikováno v:
British Journal of Radiology; Dec2023, Vol. 96 Issue 1152, p1-8, 8p
Understanding the human-object interactions (HOIs) from a video is essential to fully comprehend a visual scene. This line of research has been addressed by detecting HOIs from images and lately from videos. However, the video-based HOI anticipation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c34519fcf5757aff567138a79f1f0be4
Publikováno v:
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::950e1f063b133c514a404a76a0cf7048
https://doi.org/10.1109/wacv56688.2023.00599
https://doi.org/10.1109/wacv56688.2023.00599
Publikováno v:
2022 IEEE Globecom Workshops (GC Wkshps).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d23edbe54c9b6de2deca910e8c93dc44
https://doi.org/10.1109/gcwkshps56602.2022.10008641
https://doi.org/10.1109/gcwkshps56602.2022.10008641
Publikováno v:
IEEE Robotics and Automation Letters. 5:3501-3508
This paper proposes a framework which is able to generate a sequence of three-dimensional human dance poses for a given music. The proposed framework consists of three components: a music feature encoder, a pose generator, and a music genre classifie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::afbebe924ae3c3db6b5d3797bcbf2fb6
https://doi.org/10.1109/lra.2020.2977333
https://doi.org/10.1109/lra.2020.2977333
Autor:
Dong Wook Kim, Hyemin Ahn, Kyung Won Kim, Seung Soo Lee, Hwa Jung Kim, Yousun Ko, Taeyong Park, Jeongjin Lee
Publikováno v:
Korean Journal of Radiology; Nov2022, Vol. 23 Issue 11, p1055-1066, 15p
Publikováno v:
ICRA
In this paper, we present self-supervised shared latent embedding (S3LE), a data-driven motion retargeting method that enables the generation of natural motions in humanoid robots from motion capture data or RGB videos. While it requires paired data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5bb254ba4c012a54b6efa840a497ae55
http://arxiv.org/abs/2103.06447
http://arxiv.org/abs/2103.06447