| 2021 | ICRA | Sim-to-Real Visual Grasping via State Representation Learning Based on Combining Pixel-Level and Feature-Level Domain Adaptation. | Youngbin Park, Sang Hyoung Lee, Il Hong Suh |
| 2021 | IROS | Acceleration of Actor-Critic Deep Reinforcement Learning for Visual Grasping by State Representation Learning Based on a Preprocessed Input Image. | Tae Won Kim, Yeseong Park, Youngbin Park, Sang Hyoung Lee, Il Hong Suh |
| 2019 | IROS | Object Singulation by Nonlinear Pushing for Robotic Grasping. | Jongsoon Won, Youngbin Park, Byung-Ju Yi, Il Hong Suh |
| 2016 | ICONIP | Predicting Multiple Pregrasping Poses by Combining Deep Convolutional Neural Networks with Mixture Density Networks. | Sungphill Moon, Youngbin Park, Il Hong Suh |
| 2013 | ICONIP | Empirical Evaluation on Deep Learning of Depth Feature for Human Activity Recognition. | Junik Jang, Youngbin Park, Il Hong Suh |
| 2012 | ICRA | Lateral and feedback schemes for the inhibition of false-positive responses in edge orientation channels. | Youngbin Park, Il Hong Suh |
| 2012 | IROS | Dependable dense stereo matching by both two-layer recurrent process and chaining search. | Sehyung Lee, Youngbin Park, Il Hong Suh |
| 2010 | ICPR | Visual Recognition of Types of Structural Corridor Landmarks Using Vanishing Points Detection and Hidden Markov Models. | Youngbin Park, Sung Su Kim, Il Hong Suh |
| 2010 | RO-MAN | Predictive visual recognition of types of structural corridor landmarks for mobile robot navigation. | Youngbin Park, Il Hong Suh |
| 2009 | IROS | Bayesian robot localization with action-associated sparse appearance-based map in a dynamic indoor environment. | Youngbin Park, Il Hong Suh, Byung-Uk Choi |
| 2008 | IROS | Hierarchical Abstraction of World Elements and Behaviors for efficient task planning of a mobile robot. | Youngbin Park, Il Hong Suh, Byung-Uk Choi |