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Seunghun Lim

ORCID: 0000-0003-0579-3735
Observed ORCID: 0000-0003-0579-3735
OpenAlex ID: A5091198405
Enhanced predictive modeling vs. LCA simulation: A comparative study on CO2 emissions from ship operations
2024 · Jaewon Jang, Seunghun Lim, et al. · Ocean Engineering · 12
Maintenance Time Prediction for Predictive Maintenance of Ship Engines
2025 · Seunghun Lim, Jungmo Oh, et al. · Applied Sciences · 11
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Hybrid Neural Network-Based Maritime Carbon Dioxide Emission Prediction: Incorporating Dynamics for Enhanced Accuracy
2025 · Seunghun Lim, Jungmo Oh · Applied Sciences · 9
Carbon Dioxide Emission Characteristics and Operation Condition Optimization for Slow-Speed and High-Speed Ship Engines
2024 · Seunghun Lim, Jinkyu Park, et al. · Applied Sciences · 7
Real-time emission prediction for ship engine using stacked time-series learning: a transformer-XGBoost hybrid framework
2025 · Seunghun Lim, Jungmo Oh · Scientific Reports · 6
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A Study on a Comparison of Greenhouse Gas Emission Results According to Actual Measurement and Domestic Calculation Method for Medium-sized Diesel Engine of Vessel
2023 · Jinkyu Park, Seunghun Lim, et al. · Transactions of Korean Society of Automotive Engineers · 3
Automated Detection of IQI Wires and Weld Defects in Ship Pipe Radiographic Images Using Deep Object Detection Model
2026 · Shinhyo Kim, Seunghun Lim, et al. · International Conference on Artificial Intelligence in Information and Communication (ICAIIC)
Deep-learning-based object detection for automated IQI evaluation in analog film radiographic images of piping welds
2025 · Seunghun Lim, Shinhyo Kim, et al. · Journal of Advanced Marine Engineering and Technology
Works count: 8
Citation count: 48
H-index: 5
I10-index: 2
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