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Cyber-Energy Systems and Intelligent Energy (ICCSIE), International Conference on

作者： Junnan Li Xiaoping Wang the School of Artificial Intelligence and Automation and the Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan P. R. China

Temporal concept shift (TCS) is an unavoidable problem in physiological signal-based emotion recognition tasks, i.e., the data distribution of physiological signals is constantly changing over time, which gradually degrades the model accuracy. To this end, we propose a method based on a combination of domain adaptation and incremental learning to reduce the impact of temporal concept drift. In this paper, domain adaptation is used to reduce the distribution differences and incremental learning is used to prevent the learned knowledge from being forgotten. Finally, we validate the effectiveness of our approach on two real datasets.

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Energy Management Strategies for PEMFC-Lithium Battery Hybrid Power Systems Based on Pt Degradation

Energy Management Strategies for PEMFC-Lithium Battery Hybri...

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第42届中国控制会议

作者： Ziang Guo Beijia Li Linghong Zeng Jun Fu Chuang Sheng Xi Li School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science and Technology Shenzhen Huazhong University of Science and Technology Research Institute

Proton Exchange Membrane Fuel Cells(PEMFCs) are prone to decreased lifespan due to the degradation of the platinum(Pt) catalyst during *** this study,we have established a one-dimensional model to investigate the effects of different voltage conditions on Pt *** potential is found to be the most significant factor affecting the *** exposure to high potentials will significantly reduce the PEMFC's lifespan,and frequent voltage changes will exacerbate the *** mitigate this issue,we have designed three energy management strategies with different limitations and simulated their performance in the operating scenario of a fuel-cell hybrid electric vehicle(FCHEV).The results demonstrate that strategies restricting high potential occurrences and voltage variations can effectively alleviate Pt degradation.

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3D Cinemagraphy from a Single image

3D Cinemagraphy from a Single Image

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Xingyi Li Zhiguo Cao Huiqiang Sun Jianming Zhang Ke Xian Guosheng Lin Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology S-Lab Nanyang Technological University Adobe Research

We present 3D Cinemagraphy, a new technique that mar-ries 2D image animation with 3D photography. Given a single still image as input, our goal is to generate a video that contains both visual content animation and camera motion. We empirically find that naively combining existing 2D image animation and 3D photography methods leads to obvious artifacts or inconsistent animation. Our key insight is that representing and animating the scene in 3D space offers a natural solution to this task. To this end, we first convert the input image into feature-based layered depth images using predicted depth values, followed by unprojecting them to a feature point cloud. To animate the scene, we perform motion estimation and lift the 2D motion into the 3D scene flow. Finally, to resolve the problem of hole emer-gence as points move forward, we propose to bidirectionally displace the point cloud as per the scene flow and synthe-size novel views by separately projecting them into target image planes and blending the results. Extensive experiments demonstrate the effectiveness of our method. A user study is also conducted to validate the compelling rendering results of our method.

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HyRSM++: Hybrid Relation Guided Temporal Set Matching for Few-shot Action Recognition

arXiv

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arXiv 2023年

作者： Wang, Xiang Zhang, Shiwei Qing, Zhiwu Zuo, Zhengrong Gao, Changxin Jin, Rong Sang, Nong Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology China Alibaba Group China Twitter United States

Few-shot action recognition is a challenging but practical problem aiming to learn a model that can be easily adapted to identify new action categories with only a few labeled samples. Recent attempts mainly focus on learning deep representations for each video individually under the episodic meta-learning regime and then performing temporal alignment to match query and support videos. However, they still suffer from two drawbacks: (i) learning individual features without considering the entire task may result in limited representation capability, and (ii) existing alignment strategies are sensitive to noises and misaligned instances. To handle the two limitations, we propose a novel Hybrid Relation guided temporal Set Matching (HyRSM++) approach for few-shot action recognition. The core idea of HyRSM++ is to integrate all videos within the task to learn discriminative representations and involve a robust matching technique. To be specific, HyRSM++ consists of two key components, a hybrid relation module and a temporal set matching metric. Given the basic representations from the feature extractor, the hybrid relation module is introduced to fully exploit associated relations within and cross videos in an episodic task and thus can learn task-specific embeddings. Subsequently, in the temporal set matching metric, we carry out the distance measure between query and support videos from a set matching perspective and design a bidirectional Mean Hausdorff Metric to improve the resilience to misaligned instances. In addition, we explicitly exploit the temporal coherence in videos to regularize the matching process. In this way, HyRSM++ facilitates informative correlation exchanged among videos and enables flexible predictions under the data-limited scenario. Furthermore, we extend the proposed HyRSM++ to deal with the more challenging semi-supervised few-shot action recognition and unsupervised few-shot action recognition tasks. Experimental results on multiple benchmark

关键词： Benchmarking

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A novel method of constructing high-dimensional digital chaotic systems on finite-state automata

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Chinese Physics B 2020年第9期29卷 233-243页

作者： Jun Zheng Han-Ping Hu School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Image Information Processing and Intelligent Control Ministry of EducationWuhan 430074China

When chaotic systems are implemented on finite precision machines, it will lead to the problem of dynamical degradation. Aiming at this problem, most previous related works have been proposed to improve the dynamical degradation of low-dimensional chaotic maps. This paper presents a novel method to construct high-dimensional digital chaotic systems in the domain of finite computing precision. The model is proposed by coupling a high-dimensional digital system with a continuous chaotic system. A rigorous proof is given that the controlled digital system is chaotic in the sense of Devaney's definition of chaos. Numerical experimental results for different high-dimensional digital systems indicate that the proposed method can overcome the degradation problem and construct high-dimensional digital chaos with complicated dynamical properties. Based on the construction method, a kind of pseudorandom number generator (PRNG) is also proposed as an application.

关键词： high-dimensional digital chaotic system dynamical degradation anti-control pseudorandom number generator

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Lifetime Extension control for Multi-Stack SOFC System with Inconsistent Stacks

Lifetime Extension Control for Multi-Stack SOFC System with ...

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第42届中国控制会议

作者： Zexin Li Guoqiang Liu Wei Zhao Xi Li School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science & Technology Shenzhen Huazhong University of Science and Technology Research Institute

The multi-stack fuel cell system(MFCS) is an important basis for the application of solid oxide fuel cell(SOFC)technology to large-scale power generation *** can provide higher power,longer lifetime and better *** from the single-stack fuel cell system(SFCS),there may be some inconsistencies among the stacks in the *** the inconsistencies are ignored,they will significantly affect the lifetime of the *** study focuses on the lifetime extension of multi-stack SOFC power generation systems with inconsistent *** the multi-stack system of SOFC generally cannot control the flow rate of each stack respectively,it brings a difficulty to the control of the MFCS with inconsistencies among the *** order to overcome this difficulty,this paper built a multi-stack SOFC system model,which can characterize the degradation and inconsistencies among SOFC *** then designed a power distribution strategy based on fuzzy control to extend the lifetime of the *** strategy was verified by *** simulation results show that the strategy can effectively control the inconsistencies among the stacks and significantly extend the lifetime of the MFCS.

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A Point Cloud Segmentation Method Based on Ground Point Cloud Removal and Multi-scale Twin Range image

A Point Cloud Segmentation Method Based on Ground Point Clou...

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第42届中国控制会议

作者： Yicheng Zhou Gang Peng Hangqi Duan Zhangang Wu Xukang Zhu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Ministry of Education Shantui Construction Machinery Co. Ltd.

Aiming at the shortcomings of traditional point cloud segmentation algorithms, this paper proposes a 3D lidar point cloud segmentation method combining ground filtering and multi-scale twin range image construction. This method fully considers the geometric space distribution characteristics of the point cloud and the randomness of the positions between *** on the assumption of multi plane model, the point cloud is divided into sectors. The ground points are removed through region ground plane fitting and growth, and then the multi-scale twin range image is constructed according to non-ground *** the basis of the twin range image, the Breadth First Search algorithm is improved, the depth-breadth joint search strategy is proposed, all the points to be clustered are traversed, and the adaptive clustering threshold is used for point cloud clustering,which realizes a point cloud segmentation method with higher accuracy and robustness. Through the experimental analysis of KITTI dataset and collected campus outdoor scene dataset, compared with the traditional point cloud segmentation algorithm,the method proposed in this paper can effectively improve the point cloud segmentation accuracy and robustness of mobile robots in complex environments.

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Multimodal Brain-Computer Interfaces: AI-powered Decoding Methodologies

arXiv

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arXiv 2025年

作者： Li, Siyang Wang, Hongbin Chen, Xiaoqing Wu, Dongrui The Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The Henan Key Laboratory of Brain Science and Brain Computer Interface Technology School of Electrical and Information Engineering Zhengzhou University China

Brain-computer interfaces (BCIs) enable direct communication between the brain and external devices. This review highlights the core decoding algorithms that enable multimodal BCIs, including a dissection of the elements, a unified view of diversified approaches, and a comprehensive analysis of the present state of the field. We emphasize algorithmic advancements in cross-modality mapping, sequential modeling, besides classic multi-modality fusion, illustrating how these novel AI approaches enhance decoding of brain data. The current literature of BCI applications on visual, speech, and affective decoding are comprehensively explored. Looking forward, we draw attention on the impact of emerging architectures like multimodal Transformers, and discuss challenges such as brain data heterogeneity and common errors. This review also serves as a bridge in this interdisciplinary field for experts with neuroscience background and experts that study AI, aiming to provide a comprehensive understanding for AI-powered multimodal BCIs. © 2025, CC BY-NC-ND.

关键词： Brain computer interface

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Modeling of Solid Oxide Electrolysis Cell with Oxygen Pressure at the Oxygen electrode/Electrolyte Interface

Modeling of Solid Oxide Electrolysis Cell with Oxygen Pressu...

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第34届中国控制与决策会议

作者： Zhiping Xia Xi Li School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science & Technology

As one of the key degradation mechanisms of Solid oxide electrolysis cell(SOEC),oxygen electrode delamination directly affects the durability of *** order to improve the service life of SOEC stack,optimizing the system regulation range is an effective *** this study,according to the delamination mechanism of SOEC oxygen electrode,based on the existing thermal and electrical characteristics of the SOEC stack,a new gas characteristic of oxygen electrode/electrolyte interface oxygen pressure is added,and a cross-flow SOEC 2-D stack model with the oxygen electrode/electrolyte interface oxygen pressure was ***,the influence of the oxygen electrode/electrolyte interface oxygen pressure characteristics on the safe operating range of the stack is *** simulation results show that the safe operating range of the system was optimized by adding it.

关键词： Solid oxide electrolysis cell Durability Delamination mechanism 2-D model Advantage analysis

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Terahertz metamaterial narrowband absorber based on metal split ring

Terahertz metamaterial narrowband absorber based on metal sp...

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2023 Applied Optics and Photonics China: Optical Sensing, Imaging, and Display Technology and Applications;and Biomedical Optics, AOPC 2023

作者： Ji, Xiaodi Ge, Hongyi Jiang, Yuying Wu, Xuyang Jia, Zhiyuan Sun, Zhenyu Key Laboratory of Grain Information Processing and Control Henan University of Technology Ministry of Education Henan China Henan Provincial Key Laboratory of Grain Photoelectric Detection and Control Henan China College of Information Science and Engineering Henan University of Technology Henan Zhengzhou450001 China School of Artificial Intelligence and Big Data Henan University of Technology Henan Zhengzhou450001 China

ISBN: (纸本)9781510672321

Multi-band terahertz metamaterial absorbers offer new perspectives to achieve perfect absorption and multipoint information matching, which enable an ever-growing number of applications. In this study, a dual-band terahertz metamaterial absorber based on the metal split ring is designed. The absorber has perfect absorption peaks at 1.15 THz and 2.47 THz, and the absorption rate is more than 99%. The absorber produces a harp peak with a bandwidth of 0.008 at 2.47 THz, which has an extremely high quality factor of 308. The distribution of the electric field and surface current at two resonance points is analyzed using the finite element integration method. Through full wave simulation calculation, the maximum sensitivity of the analyte refractive index of the absorber is 400 GHz/RIU, and the maximum sensitivity of the thickness is 35 GHz/μm. The results show that the absorber can achieve highly sensitive detection of trace substances. © 2023 SPIE. All rights reserved.

关键词： Metamaterials

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