Optimal Path Tracking Control of Autonomous Vehicle: Adaptive Full-State Linear Quadratic Gaussian (LQG) Control. - Kibeom Lee; Seungmin Jeon; Heegwon Kim; Dongsuk Kum (IEEE Access, 2019)

Attentive Neural Controlled Differential Equations for Time-series Classification and Forecasting. - Sheo Yon Jhin; Heejoo Shin; Seoyoung Hong 001; Minju Jo; Solhee Park; Noseong Park; Seungbeom Lee; Hwiyoung Maeng; Seungmin Jeon (ICDM, 2021)

DPICT: Deep Progressive Image Compression Using Trit-Planes. - Jae-Han Lee; Seungmin Jeon; Kwang Pyo Choi; Youngo Park; Chang-Su Kim 001 (CVPR, 2022)

Practical Detectability for Persistent Lock-Free Data Structures. - Kyeongmin Cho; Seungmin Jeon; Jeehoon Kang (CoRR, 2022)

RD-Optimized Trit-Plane Coding of Deep Compressed Image Latent Tensors. - Seungmin Jeon; Jae-Han Lee; Chang-Su Kim 001 (CoRR, 2022)

Overtaking decision and trajectory planning in highway via hierarchical architecture of conditional state machine and chance constrained model predictive control. - Seungmin Jeon; Kibeom Lee; Dongsuk Kum (Robotics Auton. Syst., 2022)

Context-Based Trit-Plane Coding for Progressive Image Compression. - Seungmin Jeon; Kwang Pyo Choi; Youngo Park; Chang-Su Kim 001 (CVPR, 2023)

Scalable Object Detection on Embedded Devices Using Weight Pruning and Singular Value Decomposition. - Dohyun Ham; Jaeyeop Jeong; June-Kyoo Park; Raehyeon Jeong; Seungmin Jeon; Hyeongjun Jeon; Yewon Lim (CoRR, 2023)

Memento: A Framework for Detectable Recoverability in Persistent Memory. - Kyeongmin Cho; Seungmin Jeon; Azalea Raad; Jeehoon Kang (Proc. ACM Program. Lang., 2023)

Developing a Three-Dimensional Motion Data Analysis System Using the Hilbert-Huang Transform. - Seungmin Jeon; Hyunsoo Shin; Jungho Ahn; Haejong Joo; Liang Li; Woong Choi (GCCE, 2024)

Quantum Probabilistic Model Checking for Time-Bounded Properties. - Seungmin Jeon; Kyeongmin Cho; Chan Gu Kang; Janggun Lee; Hakjoo Oh; Jeehoon Kang (Proc. ACM Program. Lang., 2024)

Attentive neural controlled differential equations for time-series classification and forecasting. - Sheo Yon Jhin; Heejoo Shin; Sujie Kim; Seoyoung Hong 001; Minju Jo; Solhee Park; Noseong Park; Seungbeom Lee; Hwiyoung Maeng; Seungmin Jeon (Knowl. Inf. Syst., 2024)

MORDA: A Synthetic Dataset to Facilitate Adaptation of Object Detectors to Unseen Real-target Domain While Preserving Performance on Real-source Domain. - Hojun Lim; Heecheol Yoo; Jinwoo Lee; Seungmin Jeon; Hyeongseok Jeon (CoRR, 2025)