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Showing results 1 to 7 of 7

  • Woo Kyoung Han
  • 2024
  • Woo Kyoung Han. (2024). ABCD : Arbitrary Bitwise Coefficient for Dequantization. doi: 10.22677/THESIS.200000725860
  • DGIST
  • View : 139
  • Download : 0

Deep Convolutional Neural Networks for  estimating PM2.5 concentration levels

  • Kwon, Byung Jun
  • 2017
  • Kwon, Byung Jun. (2017). Deep Convolutional Neural Networks for estimating PM2.5 concentration levels. doi: 10.22677/thesis.2377545
  • DGIST
  • View : 898
  • Download : 305
  • 2022-06
  • Kim, Hyunduk. (2022-06). Development of a Real-Time Automatic Passenger Counting System using Head Detection Based on Deep Learning. Journal of Information Processing Systems, 18(3), 428–442. doi: 10.3745/JIPS.04.0246
  • Korea Information Processing Society
  • View : 210
  • Download : 0
  • Kim, Youngwook
  • Moon, Taesup
  • 2016-01
  • IEEE Geoscience and Remote Sensing Letters, v.13, no.1, pp.8 - 12
  • Institute of Electrical and Electronics Engineers Inc.
  • View : 904
  • Download : 0
  • 2016-03
  • Kim, In-Jung. (2016-03). Improving discrimination ability of convolutional neural networks by hybrid learning. International Journal on Document Analysis and Recognition, 19(1), 1–9. doi: 10.1007/s10032-015-0256-9
  • Springer Verlag
  • View : 933
  • Download : 0

Quantitative Assessment of Chest CT Patterns in COVID-19 and Bacterial Pneumonia Patients: a Deep Learning Perspective

  • Kang, Myeongkyun
  • Hong, Kyung Soo
  • Chikontwe, Philip
  • Luna, Acevedo Miguel Andres
  • Jang, Jong Geol
  • Park, Jongsoo
  • Shin, Kyeong-Cheol
  • Park, Sang Hyun
  • Ahn, June Hong
  • 2021-02
  • Kang, Myeongkyun. (2021-02). Quantitative Assessment of Chest CT Patterns in COVID-19 and Bacterial Pneumonia Patients: a Deep Learning Perspective. Journal of Korean Medical Science, 36(5), 1–14. doi: 10.3346/jkms.2021.36.e46
  • The Korean Academy of Medical Sciences
  • View : 524
  • Download : 83
  • 2023-08
  • 우정완. (2023-08). 자가학습과 지식증류 방법을 활용한 LiDAR 3차원 물체 탐지에서의 준지도 도메인 적응. 로봇학회 논문지, 18(3), 346–351. doi: 10.7746/jkros.2023.18.3.346
  • 한국로봇학회
  • View : 200
  • Download : 0
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