Loading [MathJax]/extensions/MathMenu.js
Yang Liu - IEEE Xplore Author Profile
Access provided by:

MIT Libraries

Sign Out
Access provided by:

MIT Libraries

Sign Out
ADVANCED SEARCH

Author details

< Back

Yang Liu

Publications
29
Citations
205
Publications by Year
20162025
Co-Authors:
Show All Co-Authors (48)
Image of author Yang Liu

Yang Liu

Affiliation

Intelligent Image Analysis and Understanding Lab
School of Future Technology
Dalian University of Technology, Dalian, China

Publication Topics

Biography

Yang Liu received the BSc degree from the Dalian University of Technology, in 2016. He is working toward the MSc degree in the School of Computer Science and Technology, Dalian University of Technology. His research interests include information extraction for biomedical literatures.(Based on document published on 13 June 2017).
Publications
29
Citations
205
Publications by Year
20162025
Co-Authors:
Show All Co-Authors (48)
Author's Published Works

Showing 1-25 of 29 results

  • Sort

Filter Results

Show

Sort By

Results

Two Heads are Better than One: Collaboration-Oriented Multi-Agent Exploration System

Yang Liu;Peng Zhang;Hangyou Yu;Pingping Zhang;Jie Zhao;Dong Wang;Huchuan Lu

IEEE Transactions on Cognitive and Developmental Systems
Year: 2025 | Early Access Article |
Autonomous exploration in unknown environments is a complex and formidable challenge that requires effective collaboration among multiple agents under partially observable conditions. Due to limited observations and inefficient collaboration, multi-agent exploration often suffers from excessively long exploration paths. To address this issue, this paper proposes a Collaboration-Oriented Multi-Agen...Show More

Two Heads are Better than One: Collaboration-Oriented Multi-Agent Exploration System

Yang Liu;Peng Zhang;Hangyou Yu;Pingping Zhang;Jie Zhao;Dong Wang;Huchuan Lu

Year: 2025 | Early Access Article |

EMTrack: Efficient Multimodal Object Tracking

Chang Liu;Ziqi Guan;Simiao Lai;Yang Liu;Huchuan Lu;Dong Wang

IEEE Transactions on Circuits and Systems for Video Technology
Year: 2025 | Volume: 35, Issue: 3 | Journal Article |
Multi-modal object tracking has received increasing attention, given the limitations the representation ability in certain challenging scenarios of single RGB modality. Recent prompt tuning techniques enable multimodal tracking to effectively inherit knowledge from foundation models trained with a large amount of RGB tracking data and achieve parameter-efficient training. However, few works focus ...Show More

EMTrack: Efficient Multimodal Object Tracking

Chang Liu;Ziqi Guan;Simiao Lai;Yang Liu;Huchuan Lu;Dong Wang

Year: 2025 | Volume: 35, Issue: 3 | Journal Article |

Reinforcement Learning with Model Predictive Control for Coordinated Operation of Power Plant

Chuang Wang;Qinggan Wei;Yang Liu;Jun Zhao;Wei Wang

2024 China Automation Congress (CAC)
Year: 2024 | Conference Paper |
To address the challenges of rapid and accurate regulation of power generation load due to significant model nonlinearity, strong inertia, and substantial variable coupling in the load control process of boiler and turbine units in coal-fired power plants, this paper proposes a control policy that combines model predictive control with reinforcement learning based on a multi-operating condition mo...Show More

Reinforcement Learning with Model Predictive Control for Coordinated Operation of Power Plant

Chuang Wang;Qinggan Wei;Yang Liu;Jun Zhao;Wei Wang

Year: 2024 | Conference Paper |

Operational Optimization Based on Model Adaptation for Compressed Air System

Xiangze Wang;Yang Liu;Lulu Zhong;Jun Zhao;Wei Wang

2024 14th Asian Control Conference (ASCC)
Year: 2024 | Conference Paper |
With the energy problem becoming more and more prominent, high energy consumption of the compressed air system (CAS) is widely concerned. Therefore, it is of great significance to reduce its energy waste and power consumption for energy saving and emission reduction. In this study, an online optimization method for CAS with the identification model and output modifier is proposed. Firstly, a new o...Show More

Operational Optimization Based on Model Adaptation for Compressed Air System

Xiangze Wang;Yang Liu;Lulu Zhong;Jun Zhao;Wei Wang

Year: 2024 | Conference Paper |

Interval Predictive Controller with Disturbance Observer for Gas Turbine

Han Zhang;Qinggan Wei;Yang Liu;Jun Zhao;Wei Wang

2024 14th Asian Control Conference (ASCC)
Year: 2024 | Conference Paper |
Gas turbines, crucial to the Combined Cycle Gas Turbine (CCGT), provide exceptional load-following capabilities and low emissions, which are key for enhancing the power system's capacity for deep peaking and rapid frequency regu-lation. Such advancements are vital for integrating renewable energy sources and optimizing national energy structures. As the power market increasingly focuses on stabili...Show More

Interval Predictive Controller with Disturbance Observer for Gas Turbine

Han Zhang;Qinggan Wei;Yang Liu;Jun Zhao;Wei Wang

Year: 2024 | Conference Paper |

Magic Tokens: Select Diverse Tokens for Multi-modal Object Re-Identification

Pingping Zhang;Yuhao Wang;Yang Liu;Zhengzheng Tu;Huchuan Lu

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2024 | Conference Paper |
Cited by: Papers (4)
Single-modal object re-identification (ReID) faces great challenges in maintaining robustness within complex visual scenarios. In contrast, multi-modal object ReID utilizes complementary information from diverse modalities, showing great potentials for practical applications. How-ever, previous methods may be easily affected by irrele-vant backgrounds and usually ignore the modality gaps. To addre...Show More

Magic Tokens: Select Diverse Tokens for Multi-modal Object Re-Identification

Pingping Zhang;Yuhao Wang;Yang Liu;Zhengzheng Tu;Huchuan Lu

Year: 2024 | Conference Paper |

Fantastic Animals and Where to Find Them: Segment Any Marine Animal with Dual SAM

Pingping Zhang;Tianyu Yan;Yang Liu;Huchuan Lu

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2024 | Conference Paper |
Cited by: Papers (3)
As an important pillar of underwater intelligence, Marine Animal Segmentation (MAS) involves segmenting ani-mals within marine environments. Previous methods don't excel in extracting long-range contextual features and over-look the connectivity between discrete pixels. Recently, Segment Anything Model (SAM) offers a universal frame-workfor general segmentation tasks. Unfortunately, trained with n...Show More

Fantastic Animals and Where to Find Them: Segment Any Marine Animal with Dual SAM

Pingping Zhang;Tianyu Yan;Yang Liu;Huchuan Lu

Year: 2024 | Conference Paper |

Reinforcement Learning based parameter optimization of cascade control loop in the Coke Dry Quenching System

Xiyu Quan;Yang Liu;Jie Jin;Jun Zhao;Wei Wang

2024 36th Chinese Control and Decision Conference (CCDC)
Year: 2024 | Conference Paper |
Waste heat boiler is an important part of dry quenching power generation, and its steam drum level cascade three impulse system is characterized by strong perturbation, non-linearity, strong coupling and multiple working conditions. In this paper, a reinforcement learning based parameter optimization of cascade control loop in the coke dry quenching system is proposed for such series control probl...Show More

Reinforcement Learning based parameter optimization of cascade control loop in the Coke Dry Quenching System

Xiyu Quan;Yang Liu;Jie Jin;Jun Zhao;Wei Wang

Year: 2024 | Conference Paper |

Interval Type-2 Fuzzy Deep Reinforcement Learning-Based Operational Optimization of Industrial Aerodynamic System

Lulu Zhong;Yang Liu;Linqing Wang;Jun Zhao;Wei Wang

IEEE Transactions on Instrumentation and Measurement
Year: 2024 | Volume: 73 | Journal Article |
Industrial aerodynamic system (IAS) provides the high-pressure air for consumer users, which is the primary source of power in the industrial park. Thus, their accurate measurement balance state and optimal scheduling are of paramount significance for reducing operational costs and enhancing operational efficiency. In order to solve this problem, an approach known as interval type-2 (IT2) fuzzy de...Show More

Interval Type-2 Fuzzy Deep Reinforcement Learning-Based Operational Optimization of Industrial Aerodynamic System

Lulu Zhong;Yang Liu;Linqing Wang;Jun Zhao;Wei Wang

Year: 2024 | Volume: 73 | Journal Article |

A Data-Driven State Estimation Framework for Natural Gas Networks With Measurement Noise

Yan Huang;Lin Feng;Yang Liu

IEEE Access
Year: 2023 | Volume: 11 | Journal Article |
The large-scale coverage of natural gas makes the composition structure and operation mode of natural gas network more complex, higher requirements are put forward for the effectiveness and accuracy of state estimation. The existing methods for state estimation of natural gas network with noise are all modeled after processing the data with noise, leading to the real data being distorted to a cert...Show More

A Data-Driven State Estimation Framework for Natural Gas Networks With Measurement Noise

Yan Huang;Lin Feng;Yang Liu

Year: 2023 | Volume: 11 | Journal Article |

Event-Triggered Online Scheduling for Industrial-Integrated Energy System

Yang Liu;Jun Zhao;Linqing Wang;Wei Wang

IEEE Transactions on Industrial Electronics
Year: 2023 | Volume: 70, Issue: 4 | Journal Article |
Cited by: Papers (2)
Sound scheduling and allocation of multienergy media is of paramount significance for reducing energy consumption and improving operation efficiency in an industrial-integrated energy system of a SIP, and the online optimization solution of various scheduling events can be regarded as the prerequisite for such challenging tasks. Thus, a novel granular-driven extended particle swarm optimization wi...Show More

Event-Triggered Online Scheduling for Industrial-Integrated Energy System

Yang Liu;Jun Zhao;Linqing Wang;Wei Wang

Year: 2023 | Volume: 70, Issue: 4 | Journal Article |

Unified Modeling for Multiple-Energy Coupling Device of Industrial Integrated Energy System

Yang Liu;Jun Zhao;Linqing Wang;Wei Wang

IEEE Transactions on Industrial Electronics
Year: 2023 | Volume: 70, Issue: 1 | Journal Article |
Cited by: Papers (4)
Data-driven unified modeling for multiple energy-coupling device (MECD) with considering the changing of operation modes (OMs) triggered by seasonal variation or the alteration of production rhythm is a challenging task. To overcome this, in this article, an unified modeling framework by using four-order tensor-based generalized interval type-2 fuzzy neural network is proposed, which considers the...Show More

Unified Modeling for Multiple-Energy Coupling Device of Industrial Integrated Energy System

Yang Liu;Jun Zhao;Linqing Wang;Wei Wang

Year: 2023 | Volume: 70, Issue: 1 | Journal Article |

Event-Triggered Adaptive Parameter Control for the Combined Cooling, Heating, and Power System

Yang Liu;Jun Zhao;Wei Wang

IEEE Transactions on Industrial Electronics
Year: 2022 | Volume: 69, Issue: 12 | Journal Article |
Cited by: Papers (4)
An industrial integrated energy system gathers a variety of production capacity and energy-related units, which also involves the production, transformation, and consumption of cold, heat, power, gas, etc. The combined cooling, heating, and power (CCHP) system built upon the cascade utilization of energy plays a significant role in improving the utilization rate of multiple energy resources. In th...Show More

Event-Triggered Adaptive Parameter Control for the Combined Cooling, Heating, and Power System

Yang Liu;Jun Zhao;Wei Wang

Year: 2022 | Volume: 69, Issue: 12 | Journal Article |

Differentially Private Distributed Online Optimization in Time-varying Networks via Dual Averaging Push

Yang Liu;Zhu Wang;Chaowen Zhu;Dong Wang;Wei Wang

2021 33rd Chinese Control and Decision Conference (CCDC)
Year: 2021 | Conference Paper |
Distributed online optimization allows several nodes in the network to collaboratively minimize the sum of time-varying local cost functions at each moment through information exchange. However, frequent interactions are prone to leakage of sensitive information. Meanwhile, the actual communication networks can be time-varying and unbalanced. To address such a problem, we proposed the differential...Show More

Differentially Private Distributed Online Optimization in Time-varying Networks via Dual Averaging Push

Yang Liu;Zhu Wang;Chaowen Zhu;Dong Wang;Wei Wang

Year: 2021 | Conference Paper |

Spatiotemporal Prediction for Energy System of Steel Industry by Generalized Tensor Granularity Based Evolving Type-2 Fuzzy Neural Network

Jun Zhao;Yang Liu;Witold Pedrycz;Wei Wang

IEEE Transactions on Industrial Informatics
Year: 2021 | Volume: 17, Issue: 12 | Journal Article |
Cited by: Papers (18)
Multiscale prediction analysis for the generation and consumption of by-product gas flows in various devices from the various production regions of the steel industry can be regarded as the prerequisite for energy scheduling and allocation. In this article, a generalized tensor granularity (GTG) based evolving interval type-2 (IT2) fuzzy neural network (GTG-EIT2FNN) is proposed to perform the mult...Show More

Spatiotemporal Prediction for Energy System of Steel Industry by Generalized Tensor Granularity Based Evolving Type-2 Fuzzy Neural Network

Jun Zhao;Yang Liu;Witold Pedrycz;Wei Wang

Year: 2021 | Volume: 17, Issue: 12 | Journal Article |

Social Neighborhood Graph and Multigraph Fusion Ranking for Multifeature Image Retrieval

Shenglan Liu;Muxin Sun;Lin Feng;Hong Qiao;Shuyuan Chen;Yang Liu

IEEE Transactions on Neural Networks and Learning Systems
Year: 2021 | Volume: 32, Issue: 3 | Journal Article |
Cited by: Papers (8)
A single feature is hard to describe the content of images from an overall perspective, which limits the retrieval performances of single-feature-based methods in image retrieval tasks. To fully describe the properties of images and improve the retrieval performances, multifeature fusion ranking-based methods are proposed. However, the effectiveness of multifeature fusion in image retrieval has no...Show More

Social Neighborhood Graph and Multigraph Fusion Ranking for Multifeature Image Retrieval

Shenglan Liu;Muxin Sun;Lin Feng;Hong Qiao;Shuyuan Chen;Yang Liu

Year: 2021 | Volume: 32, Issue: 3 | Journal Article |

Prediction Intervals for Granular Data Streams Based on Evolving Type-2 Fuzzy Granular Neural Network Dynamic Ensemble

Yang Liu;Jun Zhao;Wei Wang;Witold Pedrycz

IEEE Transactions on Fuzzy Systems
Year: 2021 | Volume: 29, Issue: 4 | Journal Article |
Cited by: Papers (22)
Granular data streams (GDSs) are a class of high-level abstract multitime scale description of data streams. Prediction intervals (PIs) for GDSs that provide estimated values as well as their corresponding reliability play an important role for assisting on-site workers to perceive the nonstationary environment in real time. However, constructing reliable PIs for GDSs constitutes a significant cha...Show More

Prediction Intervals for Granular Data Streams Based on Evolving Type-2 Fuzzy Granular Neural Network Dynamic Ensemble

Yang Liu;Jun Zhao;Wei Wang;Witold Pedrycz

Year: 2021 | Volume: 29, Issue: 4 | Journal Article |

Deep predictive controller designed for centrifugal compressor system anti-surge

Lulu Zhong;Yang Liu;Jun Zhao;Wei Wang

2020 Chinese Automation Congress (CAC)
Year: 2020 | Conference Paper |
Cited by: Papers (2)
Taking the characteristics of surge triggered in centrifugal compressor system as the analysis object, a class of controller termed as depth predictive controller is proposed in this study for anti-surge control in multiple-operational mode scenes, which involves the modular in terms of Depth interval predictor, operational mode discriminator and Dynamic Matrix Control (DMC) with anti-surge expert...Show More

Deep predictive controller designed for centrifugal compressor system anti-surge

Lulu Zhong;Yang Liu;Jun Zhao;Wei Wang

Year: 2020 | Conference Paper |

A Generalized Heterogeneous Type-2 Fuzzy Classifier and Its Industrial Application

Jun Zhao;Yang Liu;Linqing Wang;Wei Wang

IEEE Transactions on Fuzzy Systems
Year: 2020 | Volume: 28, Issue: 10 | Journal Article |
Cited by: Papers (15)
Recently, evolving fuzzy systems have been proved to be effective in dealing with real-time data streams. However, their fixed structures are not flexible enough to address the structural variations triggered by the changing operating conditions or system states in complex industrial environments. A novel generalized heterogeneous interval type-2 (IT2) fuzzy classifier, named as GHIT2Class, is pro...Show More

A Generalized Heterogeneous Type-2 Fuzzy Classifier and Its Industrial Application

Jun Zhao;Yang Liu;Linqing Wang;Wei Wang

Year: 2020 | Volume: 28, Issue: 10 | Journal Article |

Extracting Biomedical Events with Parallel Multi-Pooling Convolutional Neural Networks

Lishuang Li;Yang Liu;Meiyue Qin

IEEE/ACM Transactions on Computational Biology and Bioinformatics
Year: 2020 | Volume: 17, Issue: 2 | Journal Article |
Cited by: Papers (25)
Biomedical event extraction is important for medical research and disease prevention, which has attracted much attention in recent years. Traditionally, most of the state-of-the-art systems have been based on shallow machine learning methods, which require many complex, hand-designed features. In addition, the words encoded by one-hot are unable to represent semantic information. Therefore, we uti...Show More

Extracting Biomedical Events with Parallel Multi-Pooling Convolutional Neural Networks

Lishuang Li;Yang Liu;Meiyue Qin

Year: 2020 | Volume: 17, Issue: 2 | Journal Article |

Color Recognition for Rubik's Cube Robot

Lin Feng;Dong Jiang;Aibin Zhang;Shenglan Liu;Feilong Wang;Yang Liu

2019 IEEE International Conference on Smart Internet of Things (SmartIoT)
Year: 2019 | Conference Paper |
Cited by: Papers (2)
In this paper, we proposed three methods to solve color recognition of Rubik's cube, which includes one offline method and two online methods. Scatter balance & extreme learning machine (SB-ELM), an offline method, is proposed to illustrate the efficiency of training based method. We also put forward a conception of color drifting which indicates offline methods are always ineffectiveness and can ...Show More

Color Recognition for Rubik's Cube Robot

Lin Feng;Dong Jiang;Aibin Zhang;Shenglan Liu;Feilong Wang;Yang Liu

Year: 2019 | Conference Paper |

Sensor Network Oriented Human Motion Segmentation With Motion Change Measurement

Yang Liu;Lin Feng;Shenglan Liu;Muxin Sun

IEEE Access
Year: 2018 | Volume: 6 | Journal Article |
Cited by: Papers (8)
Smart Internet of Things has greatly improved the quality of human life with increasingly intelligent sensor networks. Efficient and accurate human motion time series segmentation is the key issue in human motion analysis and understanding. To realize human motion sequence segmentation, a comprehensive human motion description and an intelligent segmentation algorithm are required. Hence, this pap...Show More

Sensor Network Oriented Human Motion Segmentation With Motion Change Measurement

Yang Liu;Lin Feng;Shenglan Liu;Muxin Sun

Year: 2018 | Volume: 6 | Journal Article |

A Two-Stage Biomedical Event Trigger Detection Method Integrating Feature Selection and Word Embeddings

Xinyu He;Lishuang Li;Yang Liu;Xiaoming Yu;Jun Meng

IEEE/ACM Transactions on Computational Biology and Bioinformatics
Year: 2018 | Volume: 15, Issue: 4 | Journal Article |
Cited by: Papers (27)
Extracting biomedical events from biomedical literature plays an important role in the field of biomedical text mining, and the trigger detection is a key step in biomedical event extraction. We propose a two-stage method for trigger detection, which divides trigger detection into recognition stage and classification stage, and different features are selected in each stage. In the first stage, we ...Show More

A Two-Stage Biomedical Event Trigger Detection Method Integrating Feature Selection and Word Embeddings

Xinyu He;Lishuang Li;Yang Liu;Xiaoming Yu;Jun Meng

Year: 2018 | Volume: 15, Issue: 4 | Journal Article |

Manifold Warp Segmentation of Human Action

Shenglan Liu;Lin Feng;Yang Liu;Hong Qiao;Jun Wu;Wei Wang

IEEE Transactions on Neural Networks and Learning Systems
Year: 2018 | Volume: 29, Issue: 5 | Journal Article |
Cited by: Papers (7)
Human action segmentation is important for human action analysis, which is a highly active research area. Most segmentation methods are based on clustering or numerical descriptors, which are only related to data, and consider no relationship between the data and physical characteristics of human actions. Physical characteristics of human motions are those that can be directly perceived by human b...Show More

Manifold Warp Segmentation of Human Action

Shenglan Liu;Lin Feng;Yang Liu;Hong Qiao;Jun Wu;Wei Wang

Year: 2018 | Volume: 29, Issue: 5 | Journal Article |

Exploiting argument information to improve biomedical event trigger identification via recurrent neural networks and supervised attention mechanisms

Lishuang Li;Yang Liu

2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Year: 2017 | Conference Paper |
Cited by: Papers (10)
In biomedical research, events revealing complex relations between entities play an important role. Event trigger identification is a crucial and prerequisite step in the pipeline process of biomedical event extraction. There exist two main problems in the previous work: (1) Traditional feature-based methods often rely on human ingenuity, which is a time-consuming process. Though most representati...Show More

Exploiting argument information to improve biomedical event trigger identification via recurrent neural networks and supervised attention mechanisms

Lishuang Li;Yang Liu

Year: 2017 | Conference Paper |

IEEE Account

Purchase Details

Profile Information

Need Help?

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.