Younggyun Yu - IEEE Xplore Author Profile

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Author details

Younggyun Yu

Also published under: Yonggyun Yu

Publications

4

Citations

13

Publications by Year

20222024

Co-Authors:

Jaeho JungSoobum LeeSeunghyoung RyuHogeon SeoJunghoon Seo

Show All Co-Authors (6)

Younggyun Yu

Also published under: Yonggyun Yu

Affiliation

Korea Atomic Energy Research Institute

Yuseong-gu

Daejeon, Republic of Korea

Publication Topics

Neural Network,
Deep Learning,
Abnormal Data,
Anomaly Detection,
Anomaly Score,
Computation Time,
Convolutional Neural Network,
Data Normalization,
Deep Learning Models,
Deep Neural Network,
Mahalanobis Distance,
Normal Class

Biography

Yonggyun Yu received the B.S. and Ph.D. degrees from the Department of Mechanical Engineering, KAIST, in 2001 and 2010, respectively. Then, he worked with the Mobile Harbor Center, KAIST, as a Postdoctoral Fellow and a Research Assistant Professor. He is currently a Principal Researcher and the Research Director of the Artificial Intelligence Application & Strategy Team, Korea Atomic Energy Research Institute, Daejeon, South Korea. His expertise covers design optimization of musical instruments and nuclear reactor components. His current research interest includes the industrial application of deep learning.(Based on document published on 30 June 2022).

Publications

4

Citations

13

Publications by Year

20222024

Co-Authors:

Jaeho Jung
Soobum Lee
Seunghyoung Ryu
Hogeon Seo
Junghoon Seo

Show All Co-Authors (6)

Author's Published Works

Search History

Showing 1-14 of 14 results

Conferences (8)

Journals (4)

Early Access Articles (2)

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Zheng Guan(14)
Xue Wang(7)
Zhijun Yang(5)
Jinde Cao(4)
Chengchao Wang(3)
School of Information Science and Engineering, Yunnan University, Kunming, China(8)
School of Mathematics, Southeast University, Nanjing, China(3)
School of Information Science and Enigneering, Yunnan University, Kunming, China(1)
School of Information Science and Technology, Yunnan University, Kunming(1)
School of information science & technology, Yunnan University, Kunming, China(1)
2017 3rd IEEE International Conference on Computer and Communications (ICCC)(2)
IEEE Transactions on Consumer Electronics(2)
2009 Eighth IEEE/ACIS International Conference on Computer and Information Science(1)
2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)(1)
2019 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)(1)
IEEE(14)
Chengdu, China(2)
Changchun, China(1)
Chongqing, China(1)
Espoo, Finland(1)
Shanghai, China(1)
Source Images(5)
Fusion Performance(4)
Image Information(4)
Texture Details(4)
Visible Image Fusion(4)

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Results

A Retinex Decomposition Model-Based Deep Framework for Infrared and Visible Image Fusion

Xue Wang;Wenhua Qian;Zheng Guan;Jinde Cao;RunZhuo Ma;Chengchao Wang

IEEE Journal of Selected Topics in Signal Processing

Year: 2025 | Volume: 19, Issue: 1 | Journal Article |

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Infrared and visible image fusion (IVIF) aims to integrate complementary information between sensors and generate information-rich high-quality images. However, current methods mainly concentrate on the fusion of the source features from the sensors, ignoring the feature information mismatch caused by the property of the sensors, which results in redundant or even invalid information. To tackle th...Show More

A Retinex Decomposition Model-Based Deep Framework for Infrared and Visible Image Fusion

Xue Wang;Wenhua Qian;Zheng Guan;Jinde Cao;RunZhuo Ma;Chengchao Wang

IEEE Journal of Selected Topics in Signal Processing

Year: 2025 | Volume: 19, Issue: 1 | Journal Article |

STFuse: Infrared and Visible Image Fusion via Semisupervised Transfer Learning

Xue Wang;Zheng Guan;Wenhua Qian;Jinde Cao;Chengchao Wang;Runzhuo Ma

IEEE Transactions on Neural Networks and Learning Systems

Year: 2025 | Volume: 36, Issue: 1 | Journal Article |

Cited by: Papers (7)

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Infrared and visible image fusion (IVIF) aims to obtain an image that contains complementary information about the source images. However, it is challenging to define complementary information between source images in the lack of ground truth and without borrowing prior knowledge. Therefore, we propose a semisupervised transfer learning-based method for IVIF, termed STFuse, which aims to transfer ...Show More

STFuse: Infrared and Visible Image Fusion via Semisupervised Transfer Learning

Xue Wang;Zheng Guan;Wenhua Qian;Jinde Cao;Chengchao Wang;Runzhuo Ma

IEEE Transactions on Neural Networks and Learning Systems

Year: 2025 | Volume: 36, Issue: 1 | Journal Article |

Fusing Interaction Transition Features and Cross-Attention for Knowledge Tracing in E-Learning Systems

Jie Liu;Zheng Guan;Xue Wang;Zhijun Yang

IEEE Transactions on Consumer Electronics

Year: 2024 | Early Access Article |

E-learning systems, with their flexibility across time and location, further highlight the importance of consumer electronics in education. Knowledge tracing (KT) is a key part, which depicts the state of students’ knowledge state and predicts students’ future performance. However, due to the sparsity of data in real scenarios, the adequacy of state modeling and the accuracy of prediction are affe...Show More

Fusing Interaction Transition Features and Cross-Attention for Knowledge Tracing in E-Learning Systems

Jie Liu;Zheng Guan;Xue Wang;Zhijun Yang

IEEE Transactions on Consumer Electronics

Year: 2024 | Early Access Article |

Memory-Driven Attentive Knowledge Tracing for Implicit Inter-Question Analysis

Yujie Qian;Zheng Guan;Xue Wang;Zhijun Yang

IEEE Transactions on Consumer Electronics

Year: 2024 | Early Access Article |

Knowledge tracing (KT) plays a crucial role in personalized e-learning systems, aiming to model the current knowledge state by tracing the learner’s historical learning records to predict the learner’s future performance. However, most existing deep KT models do not take into account the correlation of questions and knowledge concepts, leading to inaccurate representations of students’ knowledge s...Show More

Memory-Driven Attentive Knowledge Tracing for Implicit Inter-Question Analysis

Yujie Qian;Zheng Guan;Xue Wang;Zhijun Yang

IEEE Transactions on Consumer Electronics

Year: 2024 | Early Access Article |

Salient Object Detection Based on High-level Semantic Guidance and Multi-modal Interaction

Chao Yang;Zheng Guan;Wenbi Ma

2024 IEEE 7th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

Year: 2024 | Conference Paper |

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Semantic information is essential in RGB-T salient object detection (SOD). Most existing methods directly input the extracted low-level features into the interaction module and utilize a simple recursive structure for prediction. Despite their excellent performance in several scenarios, they suffer from capturing and exploiting the attributes and complementary potential between different feature l...Show More

Salient Object Detection Based on High-level Semantic Guidance and Multi-modal Interaction

Chao Yang;Zheng Guan;Wenbi Ma

2024 IEEE 7th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

Year: 2024 | Volume: 7 | Conference Paper |

Knowledge Tracing with Soft Labels Via Knowledge Distillation and IRT-Based Modeling

Yu Yan;Zheng Guan;Xue Wang;Yanyou Wei;Zhijun Yang

2024 IEEE 3rd International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA)

Year: 2024 | Conference Paper |

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Knowledge tracing models capture student knowledge status through student learning records and predict student performance in the future. Currently popular deep knowledge tracing models are labeled by the rightness or wrongness of a student's answer, ignoring the impact of information such as scores, question difficulty, and individual ability, and using 0 and 1 as labels is too absolute. To this ...Show More

Knowledge Tracing with Soft Labels Via Knowledge Distillation and IRT-Based Modeling

Yu Yan;Zheng Guan;Xue Wang;Yanyou Wei;Zhijun Yang

2024 IEEE 3rd International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA)

Year: 2024 | Conference Paper |

Contrast Saliency Information Guided Infrared and Visible Image Fusion

Xue Wang;Zheng Guan;Wenhua Qian;Jinde Cao;Chengchao Wang;Chao Yang

IEEE Transactions on Computational Imaging

Year: 2023 | Volume: 9 | Journal Article |

Cited by: Papers (4)

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This study proposes an infrared and visible image fusion method based on contrast saliency information guided, termed CSFusion. On the one hand, the gradual recovery network is devised to achieve self-refining processing and cross-stage integration of encoded features. Specifically, the network establishes one-to-one feature reuse between the encoder and the decoder, which can effectively facilita...Show More

Contrast Saliency Information Guided Infrared and Visible Image Fusion

Xue Wang;Zheng Guan;Wenhua Qian;Jinde Cao;Chengchao Wang;Chao Yang

IEEE Transactions on Computational Imaging

Year: 2023 | Volume: 9 | Journal Article |

Infrared and Visible Image Fusion via Decoupling Network

Xue Wang;Zheng Guan;Shishuang Yu;Jinde Cao;Ya Li

IEEE Transactions on Instrumentation and Measurement

Year: 2022 | Volume: 71 | Journal Article |

Cited by: Papers (454)

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In general, the goal of the existing infrared and visible image fusion (IVIF) methods is to make the fused image contain both the high-contrast regions of the infrared image and the texture details of the visible image. However, this definition would lead the fusion image losing information from the visible image in high-contrast areas. For this problem, this article proposed a decoupling network-...Show More

Infrared and Visible Image Fusion via Decoupling Network

Xue Wang;Zheng Guan;Shishuang Yu;Jinde Cao;Ya Li

IEEE Transactions on Instrumentation and Measurement

Year: 2022 | Volume: 71 | Journal Article |

Reinforcement Learning Based Full Duplex Multi-user MIMO MAC Protocol (RL-MUFD)

Zheng Guan;Shengqian Yu;Ya Li;Min He

2022 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)

Year: 2022 | Conference Paper |

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A reinforcement learning based full-duplex multi- user multi-input multi-output (RL-MUFD) Multiple Access Control protocol is proposed. RL-MUFD is a centralized-control MAC protocol where an FD access point (AP) selects multiple simultaneous uplink and downlink streams from half-duplex users and bypasses channel estimation solely based on the geographic locations and the payloads of users. The obj...Show More

Reinforcement Learning Based Full Duplex Multi-user MIMO MAC Protocol (RL-MUFD)

Zheng Guan;Shengqian Yu;Ya Li;Min He

2022 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)

Year: 2022 | Conference Paper |

Intersection Dynamic Signal Control Method based on Road-segment Characteristics and Time-period Characteristics

Lin Tong;Zheng Guan;Chao Li

2019 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)

Year: 2019 | Conference Paper |

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The distribution of traffic flow at intersection is an important basis for traffic signal control, based on the characteristics of time and the characteristics of road segments that affect the dynamic changes of traffic flow, this paper proposes an adaptive control strategy for road traffic lights. Firstly, neural network technology is applied to traffic flow state analysis, scientifically define ...Show More

Intersection Dynamic Signal Control Method based on Road-segment Characteristics and Time-period Characteristics

Lin Tong;Zheng Guan;Chao Li

2019 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)

Year: 2019 | Conference Paper |

An efficient priority-based polling scheme for wireless local area network

Zhijun Yang;Weifeng Zhang;Hongwei Ding;Zheng Guan

2017 3rd IEEE International Conference on Computer and Communications (ICCC)

Year: 2017 | Conference Paper |

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Quality of service (QoS) support is a key attribute for wireless local area networks (WLAN) but is limited in 802.11-based wireless LANs. Based on the IEEE802.11 standard, we present an efficient priority-based polling scheme for WLAN. It becomes increasingly important to support delay-based quality of service in such WLANs. The new scheme differentiates priorities by various access policies which...Show More

An efficient priority-based polling scheme for wireless local area network

Zhijun Yang;Weifeng Zhang;Hongwei Ding;Zheng Guan

2017 3rd IEEE International Conference on Computer and Communications (ICCC)

Year: 2017 | Conference Paper |

Research on access network MAC protocol based on polling control mechanism in Triple play

Zhijun Yang;Zheng Guan;Hongwei Ding

2017 3rd IEEE International Conference on Computer and Communications (ICCC)

Year: 2017 | Conference Paper |

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HINOC1.0 (High performance Network over Coax) standard has matured and HINOC2.0 standard is being researched about access networks HiNOC MAC protocol in Triple play. Polling control mechanism has been abroadly implicated in the field of access network. This paper uses Markov Chain and probability generating function as analytical method and proposes a new HM_QoS model based on parallel scheduling ...Show More

Research on access network MAC protocol based on polling control mechanism in Triple play

Zhijun Yang;Zheng Guan;Hongwei Ding

2017 3rd IEEE International Conference on Computer and Communications (ICCC)

Year: 2017 | Conference Paper |

An analysis of polling access protocol for wireless sensor networking

Min He;Zheng Guan;Liyong Bao

2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)

Year: 2015 | Conference Paper |

Cited by: Papers (2)

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IEEE 802.11 PCF provides the fairly service without competition, but it is not energy efficiency, so the unnecessary energy consumption caused by empty polling of AP and idle listening of the active nodes will shorten the lifetime when the load is not heavy. A polling control protocol for wireless sensor network, namely Limited-K service Polling Schedule with Sleeping (K-PSSS) was proposed for the...Show More

An analysis of polling access protocol for wireless sensor networking

Min He;Zheng Guan;Liyong Bao

2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)

Year: 2015 | Conference Paper |

An Energy Efficient MAC Protocol for WSNs

Zheng Guan;Dongfeng Zhao

2009 Eighth IEEE/ACIS International Conference on Computer and Information Science

Year: 2009 | Conference Paper |

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Polling as one kind of the TDMA medium access control protocols has the advantage of energy conservation, however, its extensibility is not as good as that of contention-based protocol. The controllable threshold polling medium access protocol (CTP-MAC) in this paper is designed to realize the self-organizing in slot assignment and synchronization. Methods of the imbedded Markov-chain theory and t...Show More

An Energy Efficient MAC Protocol for WSNs

Zheng Guan;Dongfeng Zhao

2009 Eighth IEEE/ACIS International Conference on Computer and Information Science

Year: 2009 | Conference Paper |

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