Zobrazeno 1 - 10
of 420
pro vyhledávání: '"LEE YONGWOO"'
Autor:
Lee, Junghyun, Lee, Eunsang, Kim, Young-Sik, Lee, Yongwoo, Lee, Joon-Woo, Kim, Yongjune, No, Jong-Seon
Recent studies have explored the deployment of privacy-preserving deep neural networks utilizing homomorphic encryption (HE), especially for private inference (PI). Many works have attempted the approximation-aware training (AAT) approach in PI, chan
Externí odkaz:
http://arxiv.org/abs/2310.10349
Salient object detection (SOD) is a task that involves identifying and segmenting the most visually prominent object in an image. Existing solutions can accomplish this use a multi-scale feature fusion mechanism to detect the global context of an ima
Externí odkaz:
http://arxiv.org/abs/2303.09801
Autor:
Mert, Ahmet Can, Aikata, Kwon, Sunmin, Shin, Youngsam, Yoo, Donghoon, Lee, Yongwoo, Roy, Sujoy Sinha
Homomorphic encryption (HE) enables computation on encrypted data, and hence it has a great potential in privacy-preserving outsourcing of computations to the cloud. Hardware acceleration of HE is crucial as software implementations are very slow. In
Externí odkaz:
http://arxiv.org/abs/2210.05476
Publikováno v:
In Materials Today Quantum December 2024 4
Autor:
Chai, Seungjin, Lee, Yunji, Owens, Róisín M., Lee, Hwa-Rim, Lee, Yongwoo, Kim, Woojo, Jung, Sungjune
Publikováno v:
In Biomaterials March 2025 314
Autor:
Lee, Yongwoo1 (AUTHOR) yongwoo@inha.ac.kr
Publikováno v:
Mathematics (2227-7390). Sep2024, Vol. 12 Issue 18, p2909. 17p.
Autor:
Lee, Yongwoo1 (AUTHOR), Han, Sang Beom2 (AUTHOR), Auffarth, Gerd U.3 (AUTHOR), Son, Hyeck-Soo3 (AUTHOR), Khoramnia, Ramin3 (AUTHOR), Choi, Chul Young4 (AUTHOR) sashimi0@naver.com, Moon, Kun5 (AUTHOR), An, Sang Il5 (AUTHOR), Lee, Je Myung5 (AUTHOR), Lee, Jong Ho5 (AUTHOR)
Publikováno v:
PLoS ONE. 8/19/2024, Vol. 19 Issue 8, p1-12. 12p.
Autor:
Lee, Joon-Woo, Kang, HyungChul, Lee, Yongwoo, Choi, Woosuk, Eom, Jieun, Deryabin, Maxim, Lee, Eunsang, Lee, Junghyun, Yoo, Donghoon, Kim, Young-Sik, No, Jong-Seon
Fully homomorphic encryption (FHE) is one of the prospective tools for privacypreserving machine learning (PPML), and several PPML models have been proposed based on various FHE schemes and approaches. Although the FHE schemes are known as suitable t
Externí odkaz:
http://arxiv.org/abs/2106.07229
Publikováno v:
J. Commun. Netw., vol. 24, issue 3, Jun. 2022
In this paper, we propose a novel iterative encoding algorithm for DNA storage to satisfy both the GC balance and run-length constraints using a greedy algorithm. DNA strands with run-length more than three and the GC balance ratio far from 50\% are
Externí odkaz:
http://arxiv.org/abs/2103.03540
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