[8]
Joonhyuk Kim, Inug Yoon, G.-M. Park, and Jong-Hwan Kim "Non-Probabilistic Cosine Similarity Loss for Few-Shot Image Classification" The British Machine Vision Conference (BMVC), Manchester, England, Sep. 2020.
[7]
Joonhyuk Kim, G.-M. Park, and Jong-Hwan Kim "A Two-phase Multi-channel Classification Resonance Network" International Conference on Robot Intelligence Technology and Applications (RiTA), Daejeon, Korea, Nov. 2019.
[6]
Dick Sigmund, G.-M. Park, and Jong-Hwan Kim "Context Preference-based Deep Adaptive Resonance Theory: Integrating User Preference into Episodic Memory Encoding and Retrieval" IEEE International Joint Conference on Neural Networks (IJCNN), Alaska, USA, May. 2017.
[5]
Yong-Ho Yoo, Deok Hwa Kim, G.-M. Park, InBae Jeong, Seung-Hwan Baek, Si Jung Ryu, and Jong-Hwan Kim "Memory-based Realization of Task Intelligence for Robots in Human Environment" IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Workshop, Daejeon, Korea, Oct. 2016.
[4]
G.-M. Park, Sanghyun Cho, and Jong-Hwan Kim "Biologically-Inspired Episodic Memory Model Considering the Context Information" IEEE Conference on System, Man, and Cybernetics (SMC), Hungary, Budapest, Oct. 2016.
[3]
G.-M. Park and Jong-Hwan Kim "Deep Adaptive Resonance Theory for Learning Biologically Inspired Episodic Memory" IEEE International Joint Conference on Neural Networks (IJCNN), Vancouver, Canada, Jul. 2016.
[2]
G.-M. Park, Yong-Ho Yoo, and Jong-Hwan Kim "REM-ART: Reward-based Electromagnetic Adaptive Resonance Theory" International Conference on Artificial Intelligence (ICAI), Las Vegas, U.S.A., Jul. 2015.
[1]
G.-M. Park, Seung-Hwan Baek, and Jong-Hwan Kim "Falling Prevention System from External Disturbances for Humanoid Robots" International Conference on Robot Intelligence Technology and Applications (RiTA), Beijing, China, Nov. 2014.
[4]
G.-M. Park, Jae-Woo Choi, and Jong-Hwan Kim "Developmental Resonance Network" IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 30, no. 4, pp. 1278-1284, Apr. 2019.
[3]
G.-M. Park, Yong-Ho Yoo, Deok Hwa Kim, and Jong-Hwan Kim "Deep ART Neural Model for Biologically Inspired Episodic Memory and Its Application to Task Performance of Robots" IEEE Transactions on Cybernetics (TCYB), vol. 48, no. 6, pp. 1786-1799, Jun. 2018.
[2]
Deok Hwa Kim, G.-M. Park, Yong-Ho Yoo, InBae Jeong, and Jong-Hwan Kim "Realization of Task Intelligence for Service Robots in an Unstructured Environment" Annual Reviews in Control (IFAC), vol. 44, no. 1, pp. 9-18, Sep. 2017.
[1]
InBae Jeong, Woo-Ri Ko, G.-M. Park, Deok Hwa Kim, Yong-Ho Yoo, and Jong-Hwan Kim "Task Intelligence of Robots: Neural Model-based Mechanism of Thought and Online Motion Planning" IEEE Trans. Emerg. Topics Comput. Intell. (TETCI), vol. 1, no. 1, pp. 41-50, Feb. 2017.
[5]
E.-S. Chung, H.-W. Kim, G.-M. Park, J.-G. Park, H.-J. Song, B.-H. Yoo, and R. Han "적응형 마스킹과 비방향성 특징을 가진 언어이해생성 시스템 및 그 방법 (System and Method for Adaptive Masking and Non-Directional Language Understanding and Generation)" Korean Patent Application (10-2020-0168645), Dec. 4, 2020.
[4]
G.-M. Park, H.-W. Kim, J.-G. Park, H.-J. Song, B.-H. Yoo, E.-S. Chung, and R. Han "외부 메모리 네트워크가 결합된 자연어 처리 장치 및 학습 방법 (Device and Method for Learning Natural Language Processing Comprising External Memory Network)" Korean Patent Application (10-2020-0141061), Oct. 28, 2020.
[3]
H.-J. Song, H.-W. Kim, G.-M. Park, B.-H. Yoo, E.-S. Chung, and R. Han "다단계 검증 학습 방법 및 장치 (Method and Apparatus for Multi-level Verification Learning)" Korean Patent Application (10-2020-0104620), Aug. 20, 2020.
[2]
H.-W. Kim, G.-M. Park, J.-G. Park, H.-J. Song, B.-H. Yoo, E.-S. Chung, and R. Han "온라인 베이지안 퓨샷 학습 방법 및 장치 (Method and Apparatus for Online Bayesian Few-shot Learning)" Korean Patent Application (10-2020-0075025), Jun. 19, 2020.
[1]
B.-S. Song, G.-B. Park, and G.-M. Park "이중 광자결정 구조를 포함하는 발광 다이오드 (A Light Emitting Diode Containing a Double-Layered Photonic Crystal Structure)" Korean Patent Registration (10-1529817), Feb. 25, 2014.