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Youngbin Park
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2020 – today
- 2021
- [c12]Youngbin Park, Sang Hyoung Lee, Il Hong Suh:
Sim-to-Real Visual Grasping via State Representation Learning Based on Combining Pixel-Level and Feature-Level Domain Adaptation. ICRA 2021: 6300-6307 - [c11]Tae Won Kim, Yeseong Park, Youngbin Park, Sang Hyoung Lee, Il Hong Suh:
Acceleration of Actor-Critic Deep Reinforcement Learning for Visual Grasping by State Representation Learning Based on a Preprocessed Input Image. IROS 2021: 198-205 - 2020
- [j5]Byung Wan Kim, Youngbin Park, Il Hong Suh:
Integration of top-down and bottom-up visual processing using a recurrent convolutional-deconvolutional neural network for semantic segmentation. Intell. Serv. Robotics 13(1): 87-97 (2020) - [i2]Tae Won Kim, Yeseong Park, Youngbin Park, Il Hong Suh:
Acceleration of Actor-Critic Deep Reinforcement Learning for Visual Grasping in Clutter by State Representation Learning Based on Disentanglement of a Raw Input Image. CoRR abs/2002.11903 (2020)
2010 – 2019
- 2019
- [c10]Jongsoon Won, Youngbin Park, Byung-Ju Yi, Il Hong Suh:
Object Singulation by Nonlinear Pushing for Robotic Grasping. IROS 2019: 2402-2407 - 2018
- [j4]Chunggyeom Kim, Jinhyuk Lee, Raehyun Kim, Youngbin Park, Jaewoo Kang:
DeepNAP: Deep neural anomaly pre-detection in a semiconductor fab. Inf. Sci. 457-458: 1-11 (2018) - [j3]Jong-Bok Kim, Youngbin Park, Il Hong Suh:
Tracking human-like natural motion by combining two deep recurrent neural networks with Kalman filter. Intell. Serv. Robotics 11(4): 313-322 (2018) - 2016
- [c9]Sungphill Moon, Youngbin Park, Il Hong Suh:
Predicting Multiple Pregrasping Poses by Combining Deep Convolutional Neural Networks with Mixture Density Networks. ICONIP (3) 2016: 581-590 - [i1]Youngbin Park, Sungphill Moon, Il Hong Suh:
Tracking Human-like Natural Motion Using Deep Recurrent Neural Networks. CoRR abs/1604.04528 (2016) - 2014
- [j2]Youngbin Park, Il Hong Suh:
Oriented edge-selective band-pass filtering. Inf. Sci. 276: 80-103 (2014) - 2013
- [c8]Junik Jang, Youngbin Park, Il Hong Suh:
Empirical Evaluation on Deep Learning of Depth Feature for Human Activity Recognition. ICONIP (3) 2013: 576-583 - 2012
- [j1]Youngbin Park, Il Hong Suh:
Visual Recognition of Types of Corridor Segments for Mobile Robots. Adv. Robotics 26(16): 1915-1937 (2012) - [c7]Youngbin Park, Il Hong Suh:
Lateral and feedback schemes for the inhibition of false-positive responses in edge orientation channels. ICRA 2012: 5377-5383 - [c6]Sehyung Lee, Youngbin Park, Il Hong Suh:
Dependable dense stereo matching by both two-layer recurrent process and chaining search. IROS 2012: 5191-5196 - 2010
- [c5]Youngbin Park, Sung Su Kim, Il Hong Suh:
Visual Recognition of Types of Structural Corridor Landmarks Using Vanishing Points Detection and Hidden Markov Models. ICPR 2010: 3292-3295 - [c4]Youngbin Park, Il Hong Suh:
Predictive visual recognition of types of structural corridor landmarks for mobile robot navigation. RO-MAN 2010: 391-396
2000 – 2009
- 2009
- [c3]Youngbin Park, Il Hong Suh, Byung-Uk Choi:
Bayesian robot localization with action-associated sparse appearance-based map in a dynamic indoor environment. IROS 2009: 3459-3466 - 2008
- [c2]Youngbin Park, Il Hong Suh, Byung-Uk Choi:
Hierarchical Abstraction of World Elements and Behaviors for efficient task planning of a mobile robot. IROS 2008: 2585-2592 - 2006
- [c1]Youngbin Park, Seungdo Jeong, Il Hong Suh, Byung-Uk Choi:
Map-Building and Localization by Three-Dimensional Local Features for Ubiquitous Service Robot. ICUCT 2006: 69-79
Coauthor Index
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