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Chinese Automation Congress, CAC 2015

作者： Liu, Yali Cheng, Huan Jianhua, J. Li, Xi School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781467371896

In this paper, quantitative analysis was implemented to reveal the mechanism of temperature distributions inside cross-flow stack. For this purpose, a differential model of planar cross-flow SOFC stack was built. The effectiveness of this model on describing temperature distributions were full validated by experiments on single cell and a 40-cell stack. Then, the quantitative analysis was given from two aspects, namely heat produced by reactions and heat transmission between gases and solid layer. Particularly, we rigorously revealed the non-intuitive phenomenon that the fuel temperatures were decreasing inside SOFC stack along the fuel flow direction. Moreover, the research idea and the analytical method proposed in this paper also apply to co-flow and counter-flow SOFC. © 2015 IEEE.

关键词： Temperature distribution

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Protecting Multiple Types of Privacy Simultaneously in EEG-Based Brain-Computer Interfaces

Protecting Multiple Types of Privacy Simultaneously in EEG-B...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Meng, Lubin Jiang, Xue Jia, Tianwang Wu, Dongrui School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Wuhan China

ISBN: (纸本)9781665410205

A brain-computer interface (BCI) enables direct communication between the brain and an external device. Electroencephalogram (EEG) is the preferred input signal in non-invasive BCIs, due to its convenience and low cost. EEG-based BCIs have been successfully used in many applications, such as neurological rehabilitation, text input, games, and so on. However, EEG signals inherently carry rich personal information, necessitating privacy protection. This paper demonstrates that multiple types of private information (user identity, gender, and BCI-experience) can be easily inferred from EEG data, imposing a serious privacy threat to BCIs, To address this issue, we design perturbations to convert the original EEG data into privacy-protected EEG data, which conceal the private information while maintaining the primary BCI task performance. Experimental results demonstrated that the privacy-protected EEG data can significantly reduce the classification accuracy of user identity, gender and BCI-experience, but almost do not affect at all the classification accuracy of the primary BCI task, enabling user privacy protection in EEG-based BCIs. © 2024 IEEE.

关键词： Differential privacy

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A multi-sensor image registration method based on harris corner matching

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12th International Conference on Virtual Systems and Multimedia, VSMM 2006

作者： Mingyue, Ding Lingling, Li Chengping, Zhou Chao, Cai Image Processing and Intelligent Control Key Laboratory Huazhong University of Science and Technology Education Ministry Wuhan Hubei 430074 China

ISBN: (纸本)3540463046

In this paper, a registration method based on Harris corners is proposed. It is composed of three steps. First, corner extraction and matching. We use the gray level information around the corner to setup the correspondences, then use the affine invariant of Mahalannobis distance to remove the mismatched corner points. From this correspondence of the corner points, the affine matrix between two different images can be determined. Finally, map all points in the sensed image to the reference using the estimated transformation matrix and assign the corresponding gray level by re-sampling the image in the sensed image. Experiments with different types of multi-sensor images demonstrated the feasibility of our method. © Springer-Verlag Berlin Heidelberg 2006.

关键词： image processing

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Portrait Matting via Semantic and Detail Guidance 1

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7th Asian Conference on Pattern Recognition, ACPR 2023

作者： Wang, Deming Gao, Changxin Sang, Nong Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9783031476341

ISBN: (纸本)9783031476334

Portrait matting is a challenging computer vision task that aims to estimate the per-pixel opacity of the foreground human regions. To produce high-quality alpha mattes, the majority of available methods employ a user-supplied trimap as an auxiliary input. However, obtaining trimap is difficult, which restricts the application of these methods. Recently, trimap-free approaches have been developed, but the alpha quality is significantly lower than that of trimap-based methods due to the lack of guidance. In this paper, we propose a portrait matting framework via semantic and detail guidance. We use the mask obtained from portrait segmentation as semantic guidance to improve semantic understanding of portrait matting, and we present a detail encoder block to capture the low-level feature around the subject as detail guidance, which helps to refine alpha details, such as hair. The proposed approach achieves remarkable results on both composition and real-world benchmarks. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Semantics

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Different human behavior patterns in web surfing

Different human behavior patterns in web surfing

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International Conference on Vehicle and Mechanical Engineering and Information Technology, VMEIT 2014

作者： Pan, Jun Shan Hu, Han Ping Key Laboratory of Image Processing and Intelligent Control of Education Ministry School of Automation Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9783038350606

Recently, understanding and modeling human behavior have attracted increasing interests. In this paper, we provide some statistical research on human behavior in Web surfing during special stage called Flash Crowd(FC). Approximate entropy is used to find out the FC stage. We quantify behavior patterns by interval time between two consecutive request behaviors. Kolmogorov-Smirnov statistical test is used to estimate the appropriate probability distribution function of interval time. The results show that the request behavior patterns varied in different stages. © (2014) Trans Tech Publications, Switzerland.

关键词： Distribution functions

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An ACO-based online routing method for multiple order pickers with congestion consideration in warehouse

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Journal of intelligent Manufacturing 2016年第2期27卷 389-408页

作者： Chen, Fangyu Wang, Hongwei Xie, Yong Qi, Chao Key Laboratory of Image Processing and Intelligent Control of Education Ministry Institute of Systems Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China

One of the challenging problems in order picking is how to deal with the congestion happens in warehouse with multiple pickers. In this paper, we consider an ant colony optimization (ACO)-based online routing method to find picking routes for multiple order pickers under nondeterministic picking time. Here, a default route is formed by ACO for each single picker. Then, we coordinate these routes to alleviate congestion by dedicated rules based on indoor positioning and information sharing technologies, during order pickers serve the picking task. Our results indicate that the proposed method can achieve a reduction in the order service time primarily by coping with the congestion. We conclude that the new method is particularly effective in multiple-block picker-to-parts warehouses. © 2014, Springer Science+Business Media New York.

关键词： Ant colony optimization Congestion Multiple order pickers Routing method Warehouse management

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Combined UAMP and MF Message Passing Algorithm for Multi-Target Wideband DOA Estimation with Dirichlet Process Prior

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Tsinghua Science and Technology 2024年第4期29卷 1069-1081页

作者： Shanwen Guan Xinhua Lu Ji Li Rushi Lan Xiaonan Luo Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic TechnologyGuilin 541004China Guilin Huigu Institute of AI Industrial Technology Guilin 541004China School of Information Engineering Nanyang Institute of TechnologyNanyang 473000China

When estimating the direction of arrival (DOA) of wideband signals from multiple sources, the performance of sparse Bayesian methods is influenced by the frequency bands occupied by signals in different directions. This is particularly true when multiple signal frequency bands overlap. Message passing algorithms (MPA) with Dirichlet process (DP) prior can be employed in a sparse Bayesian learning (SBL) framework with high precision. However, existing methods suffer from either high complexity or low precision. To address this, we propose a low-complexity DOA estimation algorithm based on a factor graph. This approach introduces two strong constraints via a stretching transformation of the factor graph. The first constraint separates the observation from the DP prior, enabling the application of the unitary approximate message passing (UAMP) algorithm for simplified inference and mitigation of divergence issues. The second constraint compensates for the deviation in estimation angle caused by the grid mismatch problem. Compared to state-of-the-art algorithms, our proposed method offers higher estimation accuracy and lower complexity.

关键词： wideband direction of arrival(DOA)estimation sparse Bayesian learning(SBL) unitary approximate message passing(UAMP)algorithm Dirichlet process(DP)

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Improved taboo search algorithm for designing DNA sequences

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Progress in Natural Science:Materials International 2008年第5期18卷 623-627页

作者： Kai Zhang a, Jin Xu a,b, Xiutang Geng a, Jianhua Xiao a, Linqiang Pana, a The key laboratory of image processing and intelligent Control, Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China b School of Electronic Engineering and Computer Science, Peking University, Beijing 100871, China The Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China School of Electronic Engineering and Computer Science Peking University Beijing 100871 China

The design of DNA sequences is one of the most practical and important research topics in DNA computing. We adopt taboo search algorithm and improve the method for the systematic design of equal-length DNA sequences, which can satisfy certain combinatorial and thermodynamic constraints. Using taboo search algorithm, our method can avoid trapping into local optimization and can nd a set of good DNA sequences satisfying required constraints.

关键词： DNA computing Taboo search algorithm DNA sequence design

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intelligent multi-user detection using an artificial immune system

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Science in China(Series F) 2009年第12期52卷 2342-2353页

作者： GONG MaoGuo, JIAO LiCheng, MA WenPing & MA JingJing key laboratory of intelligent Perception and image Understanding of Ministry of Education of China Institute of intelligent Information processing, Xidian University, Xi’an 710071, China 1. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Xidian University Xi’an 710071 China 2. Institute of Intelligent Information Processing Xidian University Xi’an 710071 China

Artificial immune systems （AIS） are a kind of new computational intelligence methods which draw inspiration from the human immune system. In this study, we introduce an AIS-based optimization algorithm, called clonal selection algorithm, to solve the multi-user detection problem in code-division multipleaccess communications system based on the maximum-likelihood decision rule. Through proportional cloning, hypermutation, clonal selection and clonal death, the new method performs a greedy search which reproduces individuals and selects their improved maturated progenies after the affinity maturation process. Theoretical analysis indicates that the clonal selection algorithm is suitable for solving the multi-user detection problem. Computer simulations show that the proposed approach outperforms some other approaches including two genetic algorithm-based detectors and the matched filters detector, and has the ability to find the most likely combinations.

关键词： artificial immune systems clonal selection multi-user detection code-division multiple-access genetic algorithm

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MambaMIM: Pre-training Mamba with state space token interpolation and its application to medical image segmentation

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Medical image Analysis 2025年 103卷 103606页

作者： Tang, Fenghe Nian, Bingkun Li, Yingtai Jiang, Zihang Yang, Jie Liu, Wei Zhou, S. Kevin School of Biomedical Engineering Division of Life Sciences and Medicine University of Science and Technology of China Anhui Hefei230026 China Suzhou Institute for Advanced Research University of Science and Technology of China Jiangsu Suzhou215123 China Suzhou Institute for Advanced Research USTC Jiangsu Suzhou215123 China Department of Automation Shanghai Jiao Tong University Shanghai China Institute of Image Processing and Pattern Recognition Shanghai China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Jiangsu Provincial Key Laboratory of Multimodal Digital Twin Technology Jiangsu Suzhou215123 China State Key Laboratory of Precision and Intelligent Chemistry University of Science and Technology of China Anhui Hefei230026 China

Recently, the state space model Mamba has demonstrated efficient long-sequence modeling capabilities, particularly for addressing long-sequence visual tasks in 3D medical imaging. However, existing generative self-supervised learning methods have not yet fully unleashed Mamba's potential for handling long-range dependencies because they overlook the inherent causal properties of state space sequences in masked modeling. To address this challenge, we propose a general-purpose pre-training framework called MambaMIM, a masked image modeling method based on a novel TOKen-Interpolation strategy (TOKI) for the selective structure state space sequence, which learns causal relationships of state space within the masked sequence. Further, MambaMIM introduces a bottom-up 3D hybrid masking strategy to maintain a masking consistency across different architectures and can be used on any single or hybrid Mamba architecture to enhance its multi-scale and long-range representation capability. We pre-train MambaMIM on a large-scale dataset of 6.8K CT scans and evaluate its performance across eight public medical segmentation benchmarks. Extensive downstream experiments reveal the feasibility and advancement of using Mamba for medical image pre-training. In particular, when we apply the MambaMIM to a customized architecture that hybridizes MedNeXt and Vision Mamba, we consistently obtain the state-of-the-art segmentation performance. The code is available at: https://***/FengheTan9/MambaMIM. © 2025

关键词： image segmentation

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