Search Results - "Seo, Giup"

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  1. 1

    Deep Reinforcement Learning-Based Smart Joint Control Scheme for On/Off Pumping Systems in Wastewater Treatment Plants by Seo, Giup, Yoon, Seungwook, Kim, Myungsun, Mun, Changho, Hwang, Euiseok

    Published in IEEE access (2021)
    “…In this paper, we propose a deep reinforcement learning (DRL) based predictive control scheme for reducing the energy consumption and energy cost of pumping…”
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    Journal Article
  2. 2

    Label-Free Fault Detection Scheme for Inverters of PV Systems: Deep Reinforcement Learning-Based Dynamic Threshold by Seo, Giup, Yoon, Seungwook, Song, Junyoung, Srivastava, Ekta, Hwang, Euiseok

    Published in Applied sciences (01-02-2023)
    “…Generally, photovoltaic (PV) fault detection approaches can be divided into two groups: end-to-end and threshold methods. The end-to-end method typically uses…”
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    Journal Article
  3. 3

    A Content-assisted Dynamic PUF Key Generation Scheme Using Compressive Autoencoder for Internet-of-Things by Yoon, Seungwook, Song, Junho, Seo, Giup, Han, Seungnam, Hwang, Euiseok

    Published in IEEE sensors journal (01-08-2023)
    “…A physical unclonable function (PUF) is broadly investigated as a secret key generator for internet-of-things (IoT) devices because of its uniqueness and…”
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    Journal Article
  4. 4

    Geomixup: Robust Radio Frequency Based Indoor Localization Leveraging Geographic Information by Jeong, Minseok, Seo, Giup, Hwang, Euiseok

    “…In this paper, we address the problem of non-robustness in empirical risk minimization-based learning schemes for indoor localization using radio frequency…”
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    Conference Proceeding
  5. 5

    Lossless Data Compression with Bit-back Coding on Massive Smart Meter Data by Jeong, Heehun, Seo, Giup, Hwang, Euiseok

    “…In this paper, lossless time-series data compression scheme with bit-back asymmetric numeral systems (BB-ANS) is proposed for massive smart meter environment…”
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    Conference Proceeding
  6. 6

    Age of Information Optimization by Deep Reinforcement Learning for Random Access in Machine Type Communication by Jeong, Minseok, Seo, Giup, Hwang, Euiseok

    “…For machine type communication with random access (RA) protocol, finding optimal policy using deep reinforcement learning (DRL) is being actively investigated…”
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    Conference Proceeding