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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Changlong Jiang Yang Xiao Cunlin Wu Mingyang Zhang Jinghong Zheng Zhiguo Cao Joey Tianyi Zhou Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Alibaba Group Centre for Frontier AI Research Agency for Science Technology and Research (A*STAR) Singapore Institute of High Performance Computing Agency for Science Technology and Research (A*STAR) Singapore

3D interacting hand pose estimation from a single RGB image is a challenging task, due to serious self-occlusion and inter-occlusion towards hands, confusing similar appearance patterns between 2 hands, ill-posed joint position mapping from 2D to 3D, etc.. To address these, we propose to extend A2J-the state-of-the-art depth-based 3D single hand pose estimation method-to RGB domain under interacting hand condition. Our key idea is to equip A2J with strong local-global aware ability to well capture interacting hands' local fine details and global articulated clues among joints jointly. To this end, A2J is evolved under Transformer's non-local encoding-decoding framework to build A2J- Transformer. It holds 3 main advantages over A2J. First, self-attention across local anchor points is built to make them global spatial context aware to better capture joints' articulation clues for resisting occlusion. Secondly, each anchor point is regarded as learnable query with adaptive feature learning for facilitating pattern fitting capacity, instead of having the same local representation with the others. Last but not least, anchor point locates in 3D space instead of 2D as in A2J, to leverage 3D pose prediction. Experiments on challenging InterHand 2.6M demonstrate that, A2J-Transformer can achieve state-of-the-art model-free performance (3.38mm MPJPE advancement in 2-hand case) and can also be applied to depth domain with strong generalization. The code is avaliable at https://***/ChanglongJiangGit/A2J-Transformer.

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Technician Scheduling in IT maintenance Service Considering Task Release Time 32

Technician Scheduling in IT maintenance Service Considering ...

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32nd Chinese control And Decision Conference (CCDC)

作者： Chen-Ruiying Wang-Chengtao Liu-Zhenyuan Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Wuhan Windoor Informat Technol Co LTD Wuhan 430040 Peoples R China Educ Minist Image Proc & Intelligent Control Key Lab Wuhan 430074 Peoples R China

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158556

How to make full use of the skills of each employee in IT maintenance service, allocate limited human resources, deal quickly and effectively with the failures, this paper establishes a model of technician scheduling considering task release time in IT maintenance service. In order to solve this problem, four greedy algorithm rules are used to solve, and four neighborhood structures are designed based on the characteristics of the problem to form a variable neighborhood search algorithm. In addition, the variable neighborhood search is integrated into the genetic algorithm to solve the problem. Based on the actual case, a comparative experiment is carried out. It is concluded that incorporating the variable neighborhood search into the genetic algorithm can make the results better.

关键词： Personnel scheduling Cgreedy algorithm Cgenetic algorithm Cvariable neighborhood search

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Research on the detection method of alignment beacon based on the spatial structure feature of train bogies

Research on the detection method of alignment beacon based o...

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Chinese Automation Congress (CAC)

作者： Chong Cao Shaowei Wan Gang Peng Dingxin He Sheng Zhong Zhang Deng Wentao Guo School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan China Beijing Railway Institute of Mechanical & Electrical Engineering Group Co. Ltd. Beijing China Wuhan Lisai Technology Co. Ltd. Wuhan China

The high-speed train inspection robot needs to perform alignment parking and image acquisition at the position of the train bogie, and reliable alignment identification marks are the basis for the inspection robot to achieve highprecision alignment parking. The existing alignment method is mainly based on the way of artificial beacons, in the inspection workshop through manual laying of additional identification marks such as QR codes, magnetic stripes, RFID electronic tags, auxiliary robot alignment parking, but this type of method in beacon maintenance, laying costs and other aspects have certain limitations. Aiming at the problem, this paper proposes a vision-based bogie beacon detection method, which combines the target detection technology with the unique bogie spatial structure feature of the train, and provides reliable identification marks for the alignment and parking of the inspection robot. This method improves the alignment accuracy, reduces the cost of laying and maintaining artificial beacons, and has high application value.

关键词： Shafts Costs Wheels Object detection Inspection Maintenance engineering Feature extraction

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Lag Synchronization of Switched Neural Networks via Neural Activation Function and Applications in image Encryption

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IEEE Transactions on Neural Networks and Learning Systems 2015年第7期26卷 1493-502页

作者： Wen, Shiping Zeng, Zhigang Huang, Tingwen Meng, Qinggang Yao, Wei School of Automation Huazhong University of Science and Technology China and the Key Laboratory of Image Processing and Intelligent Control Wuhan 430074 China Texas A and M University at Qatar Doha 23874 Qatar Department of Computer Science Loughborough University Loughborough LE11 3TU United Kingdom School of Computer Science South-Central University for Nationalities Wuhan 430074 China

This paper investigates the problem of global exponential lag synchronization of a class of switched neural networks with time-varying delays via neural activation function and applications in image encryption. The controller is dependent on the output of the system in the case of packed circuits, since it is hard to measure the inner state of the circuits. Thus, it is critical to design the controller based on the neuron activation function. Comparing the results, in this paper, with the existing ones shows that we improve and generalize the results derived in the previous literature. Several examples are also given to illustrate the effectiveness and potential applications in image encryption.

关键词： Cryptography

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Stability of networked control systems under malicious attacks and bit rate constraints

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JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 2024年第18期361卷

作者： Wang, Wen-Hui Wang, Yan-Wu Hu, Meng-Jie Yang, Wu Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Wuhan 430074 Peoples R China China Univ Min & Technol Sch Informat & Control Engn Xuzhou 221000 Peoples R China Guangxi Univ Sch Elect Engn Nanning 530004 Peoples R China

This article investigates the stability of networked control systems under two types of malicious attacks and bit rate constraints. The malicious attacks may lead to parameter mismatches, including scaling variable mismatches between the encoder and decoder sides and discrepancies between the data sent by the encoder and received by the decoder, causing system instability. To address these issues, scaling variable update rules are proposed for the encoder and decoder sides separately to mitigate the adverse effects of malicious attacks. A control strategy featuring a compensation term is designed to counteract the detrimental impacts of the mismatch. A lower bound on the bit rate is established to prevent quantization saturation and achieve exponential stability of the system. Finally, confirmatory and comparative simulations showcase the effectiveness of the theoretical insights and the merits of the proposed strategies, respectively.

关键词： Networked control system Malicious attack Bit rate constraint

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A Comparative Study of the Kalman Filter and the LSTM Network for the Remaining Useful Life Prediction of SOFC

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ENERGIES 2023年第9期16卷 3628-3628页

作者： Sheng, Chuang Zheng, Yi Tian, Rui Xiang, Qian Deng, Zhonghua Fu, Xiaowei Li, Xi Jingchu Univ Technol Sch Gen Aviat Jingmen 448000 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Educ Minist Wuhan 430074 Peoples R China Shenzhen Huazhong Univ Sci & Technol Res Inst Shenzhen 518055 Peoples R China

The solid oxide fuel cell (SOFC) system is complicated because the characteristics of gas, heat, and electricity are intricately coupled. During the operation of the system, problems such as frequent failures and a decrease in the stack's performance have caused the SOFC system to work less well and greatly shortened the SOFC's practical life. As such, it is essential to accurately forecast its remaining useful life (RUL) to make the system last longer and cut down on economic losses. In this study, both model-based and data-driven prediction methods are used to make predictions about the RUL of SOFC. First, the linear degradation model of the SOFC system is established by introducing degradation resistance as the index of health status. Using the Kalman filtering (KF) method, the health status of SOFC is evaluated online. The results of the health state estimation indicated that the KF algorithm is accurate enough to provide a good basis for the model-based RUL prediction. Then, a long short-term memory (LSTM) network-recursive (data-driven) method is presented for RUL prognostics. The multi-step-ahead recursive strategy of updating the network state with actual test data improves the prediction accuracy. Finally, a comparison is made between the LSTM network prediction approach suggested and the model-based KF prognostics. The results of the experiments indicate that the LSTM network is more suitable for RUL prediction than the KF algorithm.

关键词： SOFC remaining useful life prediction Kalman filtering long short-term memory network

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Watch the Speakers: A Hybrid Continuous Attribution Network for Emotion Recognition in Conversation With Emotion Disentanglement

Watch the Speakers: A Hybrid Continuous Attribution Network ...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Shanglin Lei Xiaoping Wang Guanting Dong Jiang Li Yingjian Liu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing China Institute of Artificial Intelligence Huazhong University of Science and Technology (HUST) Wuhan China

Emotion Recognition in Conversation (ERC) has attracted widespread attention in the natural language processing field due to its enormous potential for practical applications. Existing ERC methods face challenges in achieving generalization to diverse scenarios due to insufficient modeling of context, ambiguous capture of dialogue relationships and overfitting in speaker modeling. In this work, we present a Hybrid Continuous Attributive Network (HCAN) to address these issues in the perspective of emotional continuation and emotional attribution. Specifically, HCAN adopts a hybrid recurrent and attention-based module to model global emotion continuity. Then a novel Emotional Attribution Encoding (EAE) is proposed to model intra- and inter-emotional attribution for each utterance. Moreover, aiming to enhance the robustness of the model in speaker modeling and improve its performance in different scenarios, A comprehensive loss function emotional cognitive loss $\mathcal{L}_{EC}$ is proposed to alleviate emotional drift and overcome the overfitting of the model to speaker modeling. Our model achieves state-of-the-art performance on three datasets, demonstrating the superiority of our work. Another extensive comparative experiments and ablation studies on three benchmarks are conducted to provided evidence to support the efficacy of each module. Further exploration of generalization ability experiments shows the plug-and-play nature of the EAE module in our method.

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Picture array generation using flat splicing operation

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Journal of Computational and Theoretical Nanoscience 2016年第6期13卷 3568-3577页

作者： Pan, Linqiang Nagar, Atulya K. Subramanian, K.G. Song, Bosheng School of Electric and Information Engineering Zhengzhou University of Light Industry Zhengzhou Henan450002 China Department of Mathematics and Computer Science Faculty of Science Liverpool Hope University LiverpoolL16 9JD United Kingdom Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan Hubei430074 China

The operation of splicing on words was introduced by Tom Head while proposing a theoretical model of DNA recombination. Subsequent investigations on splicing on linear and circular strings of symbols have resulted in a number of theoretical properties. A different kind of splicing on two words, referred to as flat splicing, has been considered recently. This operation is extended to flat splicing on picture arrays, thus defining a new model of generation of digitized pictures, which is called as array flat splicing system (AFS). Results on the generative power of AFS in comparison with certain well-known picture array defining models and certain non-closure results are obtained. Copyright © 2016 American Scientific Publishers. All rights reserved.

关键词： Nanoscience

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Modelling brain based on canonical ensemble with functional MRI: A thermodynamic exploration on neural system

arXiv

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arXiv 2021年

作者： Li, Wei Zhou, Chenxi Yang, Bin Fan, Wenliang Chen, Xi School of Artificial Intelligence and Automation Huazhong University of Science and Technology WuhanHubei430074 China Image Processing and Intelligent Control Key Laboratory of the Education Ministry of China WuhanHubei430074 China Department of Radiology Union Hospital Tongji Medical College Huazhong University of Science and Technology WuhanHubei430074 China

Objective. Modelling is an important way to study the working mechanism of brain. While the characterization and understanding of brain are still inadequate. This study tried to build a model of brain from the perspective of thermodynamics at system level, which brought a new thinking to brain modelling. Approach. Regarding brain regions as systems, voxels as particles, and intensity of signals as energy of particles, the thermodynamic model of brain was built based on canonical ensemble theory. Two pairs of activated regions and two pairs of inactivated brain regions were selected for comparison in this study, and the analysis on thermodynamic properties based on the model proposed were performed. In addition, the thermodynamic properties were also extracted as input features for the detection of Alzheimer's disease. Main results. The experiment results verified the assumption that the brain also follows the thermodynamic laws. It demonstrated the feasibility and rationality of brain thermodynamic modelling method proposed, indicating that thermodynamic parameters could be applied to describe the state of neural system. Meanwhile, the brain thermodynamic model achieved much better accuracy in detection of Alzheimer's disease, suggesting the potential application of thermodynamic model in auxiliary diagnosis. Significance. (1) Instead of applying some thermodynamic parameters to analyze neural system, a brain model at system level was proposed from perspective of thermodynamics for the first time in this study. (2) The study discovered that the neural system also follows the laws of thermodynamics, which leads to increased internal energy, increased free energy and decreased entropy when system is activated. (3) The detection of neural disease was demonstrated to be benefit from thermodynamic model, implying the immense potential of thermodynamics in auxiliary *** Codes 80-10, 82-10, 92B99 Copyright © 2021, The Authors. All rights reserved.

关键词： Brain

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A Visual Kinematics Calibration Method for Manipulator Based on Nonlinear Optimization

A Visual Kinematics Calibration Method for Manipulator Based...

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Chinese Automation Congress (CAC)

作者： Gang Peng Zhihao Wang Shangbin Guan Zhang Deng Wentao Guo Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Beijing Railway Institute of Mechanical & Electrical Engineering Group Co. Ltd. Beijing China Wuhan Lisai Technology Co. Ltd. Wuhan China

The traditional kinematic calibration method for manipulators requires precise three-dimensional measuring instruments to measure the end pose, which is not only expensive due to the high cost of the measuring instruments but also not applicable to all manipulators. Another calibration method uses a camera, but the system error caused by the camera’s parameters affects the calibration accuracy of the kinematics of the robot arm. In order to solve this problem, this paper reduces the dimensionality of the experimental data and redesigns the objective function to be optimized. That is, the three-dimensional positions of the feature points of the calibration plate under each manipulator attitude corresponding to the actual kinematic model and the classic D-H kinematic model are mapped into the pixel coordinate system, and the sum of Euclidean distance errors of the pixel coordinates of the two is used as the objective function to be optimized. And then, nonlinear optimization and parameter compensation are performed. The experimental results show that the pixel deviation of the end pose corresponding to the optimized D-H kinematic model proposed in this paper and the end pose corresponding to the actual kinematic model in the pixel coordinate system is 0.99 pixels. Compared with the 7.9 deviation pixels between the pixel coordinates calculated by the classic D-H kinematic model and the actual pixel coordinates, the deviation is reduced by nearly 7 pixels for an 87% reduction in error. Therefore, the proposed method can effectively avoid system errors caused by camera parameters in visual calibration, can improve the absolute positioning accuracy of the end of the robotic arm, and has good economy and universality.

关键词： Visualization Robot kinematics Instruments Robot vision systems Kinematics Manipulators Cameras

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