[17]
K.-H. Park, Kyungwoo Song†, and G.-M. Park† "Pre-trained Vision and Language Transformers Are Few-Shot Incremental Learners" Computer Vision and Pattern Recognition (CVPR), Seattle, U.S.A, Jun. 2024.
[16]
J. Seo*, S.-H. Lee*, T.-Y. Lee*, Seung-Jun Moon, and G.-M. Park† "Generative Unlearning for Any Identity" Computer Vision and Pattern Recognition (CVPR), Seattle, U.S.A, Jun. 2024.
[15]
S.-A. Choe*, A.-H. Shin*, K.-H. Park, Jinwoo Choi†, and G.-M. Park† "Open-Set Domain Adaptation for Semantic Segmentation" Computer Vision and Pattern Recognition (CVPR), Seattle, U.S.A, Jun. 2024.
[14]
Dongyeun Lee*, Chaewon Kim*, Sangjoon Yu, Jaejun Yoo†, and G.-M. Park† "RADIO: Reference-Agnostic Dubbing Video Synthesis" Winter Conference on Applications of Computer Vision (WACV), Waikoloa, U.S.A, Jan. 2024.
[13]
Hyogun Lee*, Kyungho Bae*, Seong Jong Ha, Yumin Ko, G.-M. Park†, and Jinwoo Choi† "GLAD: Global-Local View Alignment and Background Debiasing for Video Domain Adaptation" Winter Conference on Applications of Computer Vision (WACV), Waikoloa, U.S.A, Jan. 2024.
[12]
J.-Y. Moon*, K.-H. Park*, Jung Uk Kim†, and G.-M. Park† "Online Class Incremental Learning on Stochastic Blurry Task Boundary via Mask and Visual Prompt Tuning" International Conference on Computer Vision (ICCV), Paris, France, Oct. 2023.
[11]
J. Seo*, Ji-Su Kang*, and G.-M. Park "LFS-GAN: Lifelong Few-Shot Image Generation" International Conference on Computer Vision (ICCV), Paris, France, Oct. 2023.
[10]
Yong Hyun Ahn, G.-M. Park†, and Seong Tae Kim† "LINe: Out-of-Distribution Detection by Leveraging Important Neurons" Computer Vision and Pattern Recognition (CVPR), Vancouver, Canada, Jun. 2023.
[9]
Seungjun Moon and G.-M. Park "IntereStyle: Encoding an Interest Region for Robust StyleGAN Inversion" European Conference on Computer Vision (ECCV), Tel-Aviv, Israel, Oct. 2022.
[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.
[8]
A.-H. Shin, Seong Tae Kim†, and G.-M. Park† "Time Series Anomaly Detection using Transformer-based GAN with Two-Step Masking" IEEE Access, vol.11, no.1, pp. 74035-74047, Jul. 2023.
[7]
Jae-Woo Choi, G.-M. Park, and Jong-Hwan Kim "SR-EM: Episodic Memory Aware of Semantic Relations Based on Hierarchical Clustering Resonance Network" IEEE Transactions on Cybernetics (TCYB), vol. 52, no. 10, pp. 10339-10351, Oct. 2022.
[6]
G.-M. Park and Jong-Hwan Kim "Adaptive Developmental Resonance Network" IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 32, no. 10, pp. 4347-4361, Oct. 2021.
[5]
G.-M. Park, Sahng-Min Yoo, and Jong-Hwan Kim "Convolutional Neural Network with Developmental Memory for Continual Learning" IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 32, no. 6, pp. 2691-2705, Jun. 2021.
[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.
[18]
Cherrie Kim, Seonguk Kim, Jae-Woo Choi and G.-M. Park "Enhanced Backchannel Prediction Model Using Transformer and Loss Improvement" Korea Software Congress (KSC), Busan, Republic of Korea, Dec. 2023.
[17]
M.-J. Kim, J.-Y. Moon and G.-M. Park "Backchannel Prediction Model using Prototype Prompting" Korea Software Congress (KSC), Busan, Republic of Korea, Dec. 2023.
[16]
S.-H. Lee, T.-Y. Lee and G.-M. Park "OutLaST: Out-of-Distribution-based Continual Learning via Sample Selection and Task Prediction" Korea Software Congress (KSC), Busan, Republic of Korea, Dec. 2023.
[15]
T.-Y. Lee and G.-M. Park "Prompt based Continual Learning with OOD Score based Replay Buffer" Korea Software Congress (KSC), Jeju Island, Republic of Korea, Dec. 2022.
[14]
S.-A. Choe and G.-M. Park "Confidence-Score based Pixelwise MixUp for Unsupervised Domain Adaptation" Korea Software Congress (KSC), Jeju Island, Republic of Korea, Dec. 2022.
[13]
J.-H. Lee and G.-M. Park "Prompt Based Incremental Learning Using Attention Diversity" Korea Software Congress (KSC), Jeju Island, Republic of Korea, Dec. 2022.
[12]
J. Seo and G.-M. Park "Few-Shot Image Generation via Learning Disentangled Feature" Korea Software Congress (KSC), Jeju Island, Republic of Korea, Dec. 2022.
[11]
M.-Y. Park, K.-H. Park, and G.-M. Park “Dynamic and Assistant Prompts for Class Incremental Learning” Korea Software Congress (KSC), Jeju Island, Republic of Korea, Dec. 2022.
[10]
J. Seo, Minho Park, and G.-M. Park "Few-Shot Class Incremental Learning via Subspace Regularization with Reusing Novel-Class Weights" Korea Computer Congress (KCC), Jeju Island, Republic of Korea, Jun. 2022.
[9]
Moon-Gi Cho and G.-M. Park "Lifelong Language Learning Using Pretrained Adapters" Korea Computer Congress (KCC), Jeju Island, Republic of Korea, Jun. 2022. [Award]
[8]
J.-H. Lee, T.-Y. Lee, and G.-M. Park "Vision Transformer Uncertainty Estimation With Image Tokens" Korea Computer Congress (KCC), Jeju Island, Republic of Korea, Jun. 2022.
[7]
Seng-Min Kim, Ye-Ji Kim, Ju-Hee Jung, Tae-Woo Kang, Byeol Choi, Jun-Hyeon Yoon, and G.-M. Park "Development of platform for COVID-19 vaccination review" Korea Software Congress (KSC), Pyeongchang, Republic of Korea, Dec. 2021.
[6]
Edin Lim, Chaeeun Hwang, and G.-M. Park "Self-Improving BeatGAN via Knowledge Distillation" Korea Software Congress (KSC), Pyeongchang, Republic of Korea, Dec. 2021.
[5]
Joohye Son and G.-M. Park "Text-To-Speech with Few-Shot Adaptation" Korea Software Congress (KSC), Pyeongchang, Republic of Korea, Dec. 2021.
[4]
J.-H. Lee and G.-M. Park "Vision Transformer Based Continual Learning" Korea Software Congress (KSC), Pyeongchang, Republic of Korea, Dec. 2021. [Award]
[3]
Jaehyeok Jeong, J. Hwang, and G.-M. Park "Machine Learning based Korean Spacing Correction System" Korea Computer Congress (KCC), Jeju Island, Republic of Korea, Jun. 2021.
[2]
Daeun Lee and G.-M. Park "Weight Modulation for Incremental Learning of CNN" Korea Computer Congress (KCC), Jeju Island, Republic of Korea, Jun. 2021.
[1]
A.-H. Shin and G.-M. Park "AnoFormer: Anomalous Heartbeat Detection wth Transformer-based GAN" Korea Computer Congress (KCC), Jeju Island, Republic of Korea, Jun. 2021. [Award]
[13]
G.-M. Park, J.-H. Lee, and M.-Y. Park "클러스터 기반 어댑터 변화 제어와 증분 분류기를 통한 다목적 증분 학습 장치 및 방법 (Versatile Incremental Learning Apparatus and Method using Cluster-based Adapter Shift Control and Incremental Classifier)" Korean Patent Application (10-2024-0026300), Feb. 23, 2024.
[12]
G.-M. Park and A.-H. Shin "시계열 데이터의 이상 탐지 방법 및 이를 수행하기 위한 컴퓨팅 장치 (Method for Detecting Anomaly in Time Series Data and Computing Device for Executing The Method)" US Patent Registration (11861454), Jan. 02, 2024.
[11]
G.-M. Park, J.-Y. Moon, and K.-H. Park "인공지능 기반 분류 모델의 온라인 점진 학습 방법 및 이를 수행하기 위한 컴퓨팅 장치 (Online Incremental Learning Method of Artificial Intelligence-based Classification Model and Computing Device for Performing the Same)" Korean Patent Application (10-2023-0145630), Oct. 27, 2023.
[10]
G.-M. Park, A.-H. Shin, and M.-Y. Park "학습 가능한 이상치 모방을 통한 다변량 시계열 데이터 이상치 탐지 장치 및 방법 (Apparatus and Method for Detecting of Multivariate Time-series Anomaly)" Korean Patent Application (10-2023-0145316), Oct. 27, 2023.
[9]
G.-M. Park and K.-H. Park "소수 샷 연속 학습 방법 및 이를 수행하기 위한 컴퓨팅 장치 (Few Shot Continuous Learning Method and Computing Device for Executing the Same)" Korean Patent Application (10-2023-0145315), Oct. 27, 2023.
[8]
G.-M. Park and A.-H. Shin "다변량 시계열 데이터의 이상치 탐지 방법 및 이를 수행하기 위한 컴퓨팅 장치 (Method for Detecting Anomaly in Time Series Data and Computing Device for Performing the Same)" Korean Patent Application (10-2023-0051450), Apr. 19, 2023.
[7]
G.-M. Park and A.-H. Shin "시계열 데이터의 이상 탐지 방법 및 이를 수행하기 위한 컴퓨팅 장치 (Method for Detecting Anomaly in Time Series Data and Computing Device for Executing the Method)" Korean Patent Application (10-2021-0175107), Dec. 8, 2021.
[6]
J.-H. Kim, S.-M. Yoo, J.-H. Kim, and G.-M. Park "비지도 도메인 적응 시스템 및 방법 (Unsupervised Domain Adaptation System and Method)" Korean Patent Application (10-2021-0169536), Nov. 30, 2021.
[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.