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Seunghoon Jung ORCID

The following bibliography contains all publications indexed in this database that are linked with this name as either author, editor or any other kind of contributor.

  1. Jung, Seunghoon / Jeoung, Jaewon / Hong, Taehoon / Jang, Hyounseung (2024): Vision-based multi-label detection framework for capturing occupant action and clothing information using large-scale dataset. In: Building and Environment, v. 257 (June 2024).

    https://doi.org/10.1016/j.buildenv.2024.111537

  2. Jeoung, Jaewon / Jung, Seunghoon / Hong, Taehoon / Lee, Minhyun / Koo, ChoongWan (2023): Thermal comfort prediction based on automated extraction of skin temperature of face component on thermal image. In: Energy and Buildings, v. 298 (November 2023).

    https://doi.org/10.1016/j.enbuild.2023.113495

  3. Jung, Seunghoon / Jeoung, Jaewon / Lee, Dong‐Eun / Jang, Hyounseung / Hong, Taehoon (2023): Visual–auditory learning network for construction equipment action detection. In: Computer-Aided Civil and Infrastructure Engineering, v. 38, n. 14 (July 2023).

    https://doi.org/10.1111/mice.12983

  4. Kang, Hyuna / Jung, Seunghoon / Jeoung, Jaewon / Hong, Juwon / Hong, Taehoon (2023): A bi-level reinforcement learning model for optimal scheduling and planning of battery energy storage considering uncertainty in the energy-sharing community. In: Sustainable Cities and Society, v. 94 (July 2023).

    https://doi.org/10.1016/j.scs.2023.104538

  5. Baek, Hoyoung / Jung, Seunghoon / Hong, Juwon / Hong, Taehoon (2023): Simulation-based framework for optimal construction equipment allocation considering construction noise emissions. In: Journal of Asian Architecture and Building Engineering, v. 22, n. 5 (January 2023).

    https://doi.org/10.1080/13467581.2023.2172324

  6. Jeoung, Jaewon / Jung, Seunghoon / Hong, Taehoon / Choi, Jun-Ki (2022): Blockchain-based IoT system for personalized indoor temperature control. In: Automation in Construction, v. 140 (August 2022).

    https://doi.org/10.1016/j.autcon.2022.104339

  7. Jung, Seunghoon / Jeoung, Jaewon / Hong, Taehoon (2022): Occupant-centered real-time control of indoor temperature using deep learning algorithms. In: Building and Environment, v. 208 (January 2022).

    https://doi.org/10.1016/j.buildenv.2021.108633

  8. Jung, Seunghoon / Jeoung, Jaewon / Kang, Hyuna / Hong, Taehoon (2022): 3D convolutional neural network‐based one‐stage model for real‐time action detection in video of construction equipment. In: Computer-Aided Civil and Infrastructure Engineering, v. 37, n. 1 (20 December 2022).

    https://doi.org/10.1111/mice.12695

  9. Jung, Seunghoon / Kang, Hyuna / Lee, Minhyun / Hong, Taehoon (2020): An optimal scheduling model of an energy storage system with a photovoltaic system in residential buildings considering the economic and environmental aspects. In: Energy and Buildings, v. 209 (February 2020).

    https://doi.org/10.1016/j.enbuild.2019.109701

  10. Kang, Hyuna / Hong, Taehoon / Jung, Seunghoon / Lee, Minhyun (2019): Techno-economic performance analysis of the smart solar photovoltaic blinds considering the photovoltaic panel type and the solar tracking method. In: Energy and Buildings, v. 193 (June 2019).

    https://doi.org/10.1016/j.enbuild.2019.03.042

  11. Jung, Seunghoon / Kang, Hyuna / Choi, Jinwoo / Hong, Taehoon / Seon Park, Hyo / Lee, Dong-Eun (2020): Quantitative health impact assessment of construction noise exposure on the nearby region for noise barrier optimization. In: Building and Environment, v. 176 (June 2020).

    https://doi.org/10.1016/j.buildenv.2020.106869

  12. Hong, Juwon / Kang, Hyuna / Jung, Seunghoon / Sung, Seulki / Hong, Taehoon / Seon Park, Hyo / Lee, Dong-Eun (2020): An empirical analysis of environmental pollutants on building construction sites for determining the real-time monitoring indices. In: Building and Environment, v. 170 (March 2020).

    https://doi.org/10.1016/j.buildenv.2019.106636

  13. Jung, Seunghoon / Kang, Hyuna / Sung, Seulki / Hong, Taehoon (2019): Health risk assessment for occupants as a decision-making tool to quantify the environmental effects of particulate matter in construction projects. In: Building and Environment, v. 161 (August 2019).

    https://doi.org/10.1016/j.buildenv.2019.106267

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