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arXiv 2020年

作者： Liu, Ziang Wu, Dongrui Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

In many real-world machine learning applications, unlabeled data can be easily obtained, but it is very timeconsuming and/or expensive to label them. So, it is desirable to be able to select the optimal samples to label, so that a good machine learning model can be trained from a minimum amount of labeled data. Active learning (AL) has been widely used for this purpose. However, most existing AL approaches are supervised: they train an initial model from a small amount of labeled samples, query new samples based on the model, and then update the model iteratively. Few of them have considered the completely unsupervised AL problem, i.e., starting from zero, how to optimally select the very first few samples to label, without knowing any label information at all. This problem is very challenging, as no label information can be utilized. This paper studies unsupervised pool-based AL for linear regression problems. We propose a novel AL approach that considers simultaneously the informativeness, representativeness, and diversity, three essential criteria in AL. Extensive experiments on 14 datasets from various application domains, using three different linear regression models (ridge regression, LASSO, and linear support vector regression), demonstrated the effectiveness of our proposed approach. Copyright © 2020, The Authors. All rights reserved.

关键词： Linear regression

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3D TRUS Image Segmentation in Prostate Brachytherapy

3D TRUS Image Segmentation in Prostate Brachytherapy

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Mingyue Ding L. Gardi Zhouping Wei A. Fenster Institute for Pattern Recognition and Artificial Intelligence Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China Imaging Research Laboratories Robarts Research Institute London ONT Canada

Brachytherapy is a minimally invasive interventional surgery used to treat prostate cancer. It is composed of three steps: dose pre-planning, implantation of radioactive seeds, and dose post-planning. In these procedures, it is crucial to determine the positions of needles and seeds, measure the volume of the prostate gland. Three-dimensional transrectal ultrasound (TRUS) imaging has been demonstrated to be a useful technique to perform such tasks. Compared to CT, MRI or X-ray imaging, US image suffers from low contrast, image speckle and shadows, making it challenging for segmentation of needles, the prostates and seeds in the 3D TRUS images. In this paper, we reviewed 3D TRUS image segmentation methods used in prostate brachytherapy including the segmentations of the needles, the prostate, as well as the seeds. Furthermore, some experimental results with agar phantom, turkey and chicken phantom, as well as the patient data are reported

关键词： Image segmentation Brachytherapy Needles Minimally invasive surgery Ultrasonic imaging imaging phantoms Oncological surgery Prostate cancer Position measurement Volume measurement

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Dual-Source CBCT for Larger Longitudinal Coverage: System Design and Image Reconstruction 46

Dual-Source CBCT for Larger Longitudinal Coverage: System De...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Zhang, Xusheng Lyu, Tianling Shi, Yijie Zhong, Xinyun Wu, Zhan Xi, Yan Wang, Shijie Chen, Yang Zhu, Wentao Southeast University School of Software Nanjing China Zhejiang Lab Hangzhou China First-Imaging Tech. Shanghai China Southeast University Laboratory of Image Science and Technology The School of Computer Science and Engineering Nanjing China Southeast University Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing The Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Nanjing China

ISBN: (纸本)9798350371499

The application of CBCT systems in intraoperative environments has become increasingly common, but concurrent CBCT systems are unsuitable for situations that require a large longitudinal imaging FoV, such as orthopedics. To increase longitudinal coverage, we developed a dual-source CBCT (DS-CBCT) system in which two ray sources are symmetrically placed along the central plane. After further analyzing its geometric characteristics, we propose an analytical reconstruction algorithm termed DT-FDK specialized for DS-CBCT, which combines cone-beam rebinning and two rays with smaller cone angles among the four conjugate rays to further suppress cone beam artifacts. The system design and reconstruction algorithm are tested on both simulated and real-scanned data. Results show that the DS-CBCT can expand the effective imaging volume by 37.1% compared to single-source CBCT systems. The reconstructed images by DT-FDK also show improved image quality compared to traditional reconstruction algorithms. © 2024 IEEE.

关键词： Cones

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Multi-Objective Optimal Configuration and Stable-Dynamic Management Rules of Grid-Connected Sofc/Lb Microgrids Accelerated by Energy-Based Pre-Selection

SSRN

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SSRN 2024年

作者： Yin, Zishan Tang, Xiyun Wang, Zhuo Deng, Zhonghua Li, Xi School of Artificial Intelligence and Automation Key Laboratory of Imaging Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Hubei Wuhan430074 China Wuhan Huamao Automation Co. Ltd. China

Microgrids are suitable to consume the increasing renewable sources to meet the fluctuating load demand nowadays, and configuration design is essential to build techno-economic microgrids. Solid Oxide Fuel Cell (SOFC) has high efficiency, high power output, and high fuel adaptability, which can be implemented as a controllable unit combined with an electrolyzer in hydrogen hybrid microgrids. However, the SOFC system’s slow load response should be considered due to SOFC’s complex dynamic characteristics. In this research, a grid-connected SOFC/lithium battery (LB) microgrid integrated photovoltaic and wind energy is constructed, and the LB complements the SOFC system’s slow load response. The stable-dynamic management rules are proposed, considering both SOFC’s tracking response and LB ‘s dynamic discharging and charging limitation to enhance LB’s cycle times. The minimal life cycle cost and minimal renewable energy (RS) curtailment rate are optimized by NSGA-II and the solving process is accelerated by an energy-based pre-selection method. An actual case is studied in one small region in China. The acceleration method is evaluated by comparison and the trade-off between two objectives is proved by the Pareto of the optimal solutions. To further analyze daytime management, we solve the optimal compromise solution by the fuzzy function and study the power dispatching of the typical days. © 2024, The Authors. All rights reserved.

关键词： Hydrogen

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Matrix representation of spiking neural P systems

Matrix representation of spiking neural P systems

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11th International Conference on Membrane Computing, CMC 2010

作者： Zeng, Xiangxiang Adorna, Henry Martínez-Del-Amor, Miguel Ángel Pan, Linqiang Pérez-Jiménez, Mario J. Image Processing and Intelligent Control Key Laboratory of Education Ministry Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China University of the Philippines Diliman 1101 Quezon City Philippines Research Group on Natural Computing Department of Computer Science and Artificial Intelligence University of Sevilla Avda. Reina Mercedes s/n 41012 Sevilla Spain

ISBN: (纸本)3642181228

Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. In this work, a discrete structure representation of SN P systems with extended rules and without delay is proposed. Specifically, matrices are used to represent SN P systems. In order to represent the computations of SN P systems by matrices, configuration vectors are defined to monitor the number of spikes in each neuron at any given configuration;transition net gain vectors are also introduced to quantify the total amount of spikes consumed and produced after the chosen rules are applied. Nondeterminism of the systems is assured by a set of spiking transition vectors that could be used at any given time during the computation. With such matrix representation, it is quite convenient to determine the next configuration from a given configuration, since it involves only multiplication and addition of matrices after deciding the spiking transition vector. © 2010 Springer-Verlag.

关键词： Vectors

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Compressive tracking via appearance modeling based on structural local patch

Compressive tracking via appearance modeling based on struct...

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International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)

作者： Xiaoyu Hu Hongquan Yun Delie Ming Tian Tian National Key Laboratory of Science and Technology on Multi-spectral Information Processing Huazhong University of Science and Technology Wuhan China National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing Aerospace Automatic Control Institute Beijing China

In this paper, we propose a compressive tracking method via appearance model based on structural local patchs and improved Haar-like feature. In contrast to previous compressive tracking only considering the holistic representation, an object can be represented by local image patches with spatial layout in an object. This representation takes advantage of both partial information and spatial information of the target. Each local patch has a fixed position in the target field, and all local patches can represent the whole target. In addition, our appearance model based on features extracted from image patches, which can guarantee the randomness of the rectangular boxes and the distribution of the rectangular boxes over the entire image area, avoiding the randomness of the rectangular boxes is too strong to weak the feature expression. We sample the positive and negative samples and divide them into patchs to train a binary classification via a naive Bayes classifier with online update, then the classifier is used to discriminate the candidate samples. The candidate sample which gets the highest classify score is the target. After that we draw positive and negative samples in the same way with the candidate samples to update the classifier to get ready for next frame. Our approach helps not only locate the target more accurately but also can handle partial occlusion effectively. The proposed tracker is compared with several state-of-the-art trackers on some challenging video sequences. Our proposed tracker is better and more stable in both quantitative and qualitative comparisons.

关键词： Decision support systems Target tracking Feature extraction Erbium Laboratories Aerospace control Compressed sensing

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Complementary Learning Subnetworks for Parameter-Efficient Class-Incremental Learning

arXiv

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arXiv 2023年

作者： Li, Depeng Zeng, Zhigang The School of Artificial Intelligence and Automation The Institute of Artificial Intelligence Huazhong University of Science and Technology China The Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China

In the scenario of class-incremental learning (CIL), deep neural networks have to adapt their model parameters to non-stationary data distributions, e.g., the emergence of new classes over time. However, CIL models are challenged by the well-known catastrophic forgetting phenomenon. Typical methods such as rehearsal-based ones rely on storing exemplars of old classes to mitigate catastrophic forgetting, which limits real-world applications considering memory resources and privacy issues. In this paper, we propose a novel rehearsal-free CIL approach that learns continually via the synergy between two Complementary Learning Subnetworks. Our approach involves jointly optimizing a plastic CNN feature extractor and an analytical feed-forward classifier. The inaccessibility of historical data is tackled by holistically controlling the parameters of a well-trained model, ensuring that the decision boundary learned fits new classes while retaining recognition of previously learned classes. Specifically, the trainable CNN feature extractor provides task-dependent knowledge separately without interference;and the final classifier integrates task-specific knowledge incrementally for decision-making without forgetting. In each CIL session, it accommodates new tasks by attaching a tiny set of declarative parameters to its backbone, in which only one matrix per task or one vector per class is kept for knowledge retention. Extensive experiments on a variety of task sequences show that our method achieves competitive results against state-of-the-art methods, especially in accuracy gain, memory cost, training efficiency, and task-order robustness. Furthermore, to make the non-growing backbone (i.e., a model with limited network capacity) suffice to train on more incoming tasks, a graceful forgetting implementation on previously learned trivial tasks is empirically investigated. Copyright © 2023, The Authors. All rights reserved.

关键词： Decision making

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Temperature Gradient Analyses of a Tubular Solid Oxide Fuel Cell Fueled by Methanol

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Transactions of Tianjin University 2023年第1期29卷 14-30页

作者： Qidong Xu Meiting Guo Lingchao Xia Zheng Li Qijiao He Dongqi Zhao Keqing Zheng Meng Ni Department of Building and Real Estate Research Institute for Sustainable Urban Development(RISUD)&Research Institute for Smart Energy(RISE)The Hong Kong Polytechnic UniversityHong Kong 999077China School of Artifi cial Intelligence and Automation Key Laboratory of Image Processing and Intelligent ControlHuazhong University of Science and TechnologyWuhan 430074China School of Low-Carbon Energy and Power Engineering China University of Mining and TechnologyXuzhou 221116China

Thermal management in solid oxide fuel cells(SOFC)is a critical issue due to non-uniform electrochemical reactions and convective fl ows within the ***,a 2D mathematical model is established herein to investigate the thermal responses of a tubular methanol-fueled *** show that unlike the low-temperature condition of 873 K,where the peak temperature gradient occurs at the cell center,it appears near the fuel inlet at 1073 K because of the rapid temperature rise induced by the elevated current *** the large heat convection capacity,excessive air could not eff ectively eliminate the harmful temperature gradient caused by the large current ***,optimal control of the current density by properly selecting the operating potential could generate a local thermal neutral ***,the maximum axial temperature gradient could be reduced by about 18%at 973 K and 20%at 1073 K when the air with a 5 K higher temperature is ***,despite the higher electrochemical performance observed,the cell with a counter-fl ow arrange-ment featured by a larger hot area and higher maximum temperature gradients is not preferable for a ceramic SOFC system considering thermal ***,this study could provide insightful thermal information for the operating condition selection,structure design,and stability assessment of realistic SOFCs combined with their internal reforming process.

关键词： Solid oxide fuel cell Modeling Methanol fuel Temperature gradient Internal reforming

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Model-independent event-based consensus of multiple Euler-Lagrange systems with input disturbances

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Information Sciences 2024年 675卷

作者： Long, Mingkang An, Qing Su, Housheng School of Artificial Intelligence and Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan430074 China Artificial Intelligence School Wuchang University of Technology Wuhan430223 China

This paper investigates leaderless consensus (LLC) and leader-follower consensus (LFC) issues of multiple Euler-Lagrange systems (MELSs) with uncertain system parameters and input disturbances. Firstly, by utilizing event-based control strategy, event-based consensus protocols are proposed to achieve LLC and LFC, respectively. Then, to confirm that no Euler-Lagrange (EL) system will exhibit Zeno behavior under the above event-based consensus protocols, we show that the low bound of event-triggering interval is strictly positive for any time instants. Distinct with the existing related works, the proposed event-triggered consensus protocols only rely on local sampled state, and are irrelevant to the system parameters. Finally, some simulation examples are presented to illustrate the feasibility of the proposed event-based consensus algorithms. © 2024 Elsevier Inc.

关键词： Uncertainty analysis

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Infrared image dim small target detection based-on double energy accumulation

Infrared image dim small target detection based-on double en...

引用

International Conference on Space Information Technology

作者： Sun, Yuqiu Zheng, Sheng Tian, Jinwen Liu, Jian Image Processing and Intelligence Control Key Laboratory Huazhong University of Science and Technology State Educational Ministry 430074 Wuhan Hubei China School of Information and Mathematics Yangtze University 434023 Jingzhou Hubei China Dept. of Electronic Information and Enginery Huazhong University of Science and Technology 430074 Wuhan Hubei China

ISBN: (纸本)0819460079

Detection of dim moving small targets at low signal noise ratio is a very important issue and difficult problem in infrared searching and tracking system. Based on analysis of the character of infrared images, a new double energy accumulating method is proposed. Firstly, images are denoised by wavelet transformation with soft threshold. Then, object motion area is detected according to difference images and the target intensity is well enhanced by accumulating energy two times with addition and product operation. Finally, target candidates are separated from background by thresholding process with the selected threshold. Computer experiments are carried out with an infrared image sequence and the experimental results illustrate that the proposed method is effective and efficient.

关键词： Radar target recognition

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