Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Seongbin Oh"'
Autor:
Jangsaeng Kim, Jiseong Im, Wonjun Shin, Soochang Lee, Seongbin Oh, Dongseok Kwon, Gyuweon Jung, Woo Young Choi, Jong‐Ho Lee
Publikováno v:
Advanced Science, Vol 11, Iss 26, Pp n/a-n/a (2024)
Abstract Smart healthcare systems integrated with advanced deep neural networks enable real‐time health monitoring, early disease detection, and personalized treatment. In this work, a novel 3D AND‐type flash memory array with a rounded double ch
Externí odkaz:
https://doaj.org/article/c35e803990864460a248082b776f33dd
Autor:
Jonghyun Ko, Dongseok Kwon, Joon Hwang, Kyu‐Ho Lee, Seongbin Oh, Jeonghyun Kim, Jiseong Im, Ryun‐Han Koo, Jae‐Joon Kim, Jong‐Ho Lee
Publikováno v:
Advanced Intelligent Systems, Vol 6, Iss 4, Pp n/a-n/a (2024)
Spiking neural networks (SNNs) have emerged as a novel approach for reducing computational costs by mimicking the biologically plausible operations of neurons and synapses. In this article, large‐scale analog SNNs are investigated and optimized at
Externí odkaz:
https://doaj.org/article/91c6e59905cf4bfcb02adfd2547b5a58
Autor:
Seongbin Oh, Dongseok Kwon, Gyuho Yeom, Won-Mook Kang, Soochang Lee, Sung Yun Woo, Jaehyeon Kim, Jong-Ho Lee
Publikováno v:
IEEE Access, Vol 10, Pp 24444-24455 (2022)
Hardware-based Spiking Neural Networks (SNNs) are regarded as promising candidates for the cognitive computing system due to its low power consumption and highly parallel operation. In this paper, we train the SNN in which the firing time carries inf
Externí odkaz:
https://doaj.org/article/6d382bef0479438babd911ece5619d7d
Autor:
Jiseong Im, Jaehyeon Kim, Ho-Nam Yoo, Jong-Won Baek, Dongseok Kwon, Seongbin Oh, Jangsaeng Kim, Joon Hwang, Byung-Gook Park, Jong-Ho Lee
Publikováno v:
IEEE Access, Vol 10, Pp 31263-31272 (2022)
Artificial Neural Networks (ANNs) have shown remarkable performance in various fields. However, ANN relies on the von-Neumann architecture, which consumes a lot of power. Hardware-based spiking neural networks (SNNs) inspired by a human brain have be
Externí odkaz:
https://doaj.org/article/e08780653d1f45ceb66ccb75e2463b25
Autor:
Seongbin Oh, Soochang Lee, Sung Yun Woo, Dongseok Kwon, Jiseong Im, Joon Hwang, Jong-Ho Bae, Byung-Gook Park, Jong-Ho Lee
Publikováno v:
IEEE Access, Vol 9, Pp 78098-78107 (2021)
In hardware-based spiking neural networks (SNNs), the conversion of analog input data into the arrival time of an input pulse is regarded as a good candidate for the encoding method due to its bio-plausibility and power-efficiency. In this work, we t
Externí odkaz:
https://doaj.org/article/d719f4e5a89446179b91e0c4eed28e66
Autor:
Dongseok Kwon, Suhwan Lim, Jong-Ho Bae, Sung-Tae Lee, Hyeongsu Kim, Young-Tak Seo, Seongbin Oh, Jangsaeng Kim, Kyuho Yeom, Byung-Gook Park, Jong-Ho Lee
Publikováno v:
Frontiers in Neuroscience, Vol 14 (2020)
Hardware-based spiking neural networks (SNNs) inspired by a biological nervous system are regarded as an innovative computing system with very low power consumption and massively parallel operation. To train SNNs with supervision, we propose an effic
Externí odkaz:
https://doaj.org/article/f5096bd0a86e4707923f48fb47fc3102
Autor:
Byung-Gook Park, Sung Yun Woo, Dongseok Kwon, Soochang Lee, Chul-Heung Kim, Jong-Ho Bae, Jangsaeng Kim, Won-Mook Kang, Seongbin Oh, Jong-Ho Lee
Publikováno v:
Neurocomputing. 428:153-165
Bio-inspired hardware-based spiking neural networks (SNNs) has been suggested as a promising computing system with low power consumption and parallel operation. We propose the supervised on-chip training method approximating the backpropagation algor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cc534a03f33b8bfb73b1a3805c1614ed
https://doi.org/10.1016/j.neucom.2020.11.016
https://doi.org/10.1016/j.neucom.2020.11.016
Autor:
Soochang Lee, Seongbin Oh, Sung Yun Woo, Jangsaeng Kim, Jong-Ho Lee, Won-Mook Kang, Jong-Ho Bae, Byung-Gook Park, Dongseok Kwon, Chul-Heung Kim
Publikováno v:
Neural Computing and Applications. 33:9391-9402
Reinforcement learning (RL) using deep Q-networks (DQNs) has shown performance beyond the human level in a number of complex problems. In addition, many studies have focused on bio-inspired hardware-based spiking neural networks (SNNs) given the capa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7e72d0b27eeafeedd6c212d07e10d637
https://doi.org/10.1007/s00521-021-05699-z
https://doi.org/10.1007/s00521-021-05699-z
Publikováno v:
Solid-State Electronics. 200:108566
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3843073ae69be4f3265ff82ca3bf7284
https://doi.org/10.1016/j.sse.2022.108566
https://doi.org/10.1016/j.sse.2022.108566
Autor:
Sung Yun Woo, Won-Mook Kang, Young-Tak Seo, Soochang Lee, Dongseok Kwon, Seongbin Oh, Jong-Ho Bae, Jong-Ho Lee
Publikováno v:
Solid-State Electronics. 198:108481
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9f63289ab268efb23b4d6f049439c18
https://doi.org/10.1016/j.sse.2022.108481
https://doi.org/10.1016/j.sse.2022.108481