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2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Peng, Juewen Pan, Zhiyu Liu, Chengxin Luo, Xianrui Sun, Huiqiang Shen, Liao Xian, Ke Cao, Zhiguo Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control China Nanyang Technological University S-Lab Singapore

ISBN: (纸本)9798350302493

Bokeh effect transformation is a novel task in computer vision and computational photography. It aims to convert bokeh effects from one camera lens to another. To this end, we introduce a new concept of blur ratio, which represents the ratio of the blur amount of a target image to that of a source image, and propose a novel framework SBTNet based on this concept. For cat-eye simulation and lens type transformation, a two-channel coordinate map and a two-channel one-hot map are added as extra inputs. The core of the framework is a sequence of parallel FeaNets, along with a feature selection and integration strategy, which aims to transform the blur amount with arbitrary blur ratio. The effectiveness of the proposed framework is demonstrated through extensive experiments, and our solution has achieved the top LPIPS metric in NTIRE 2023 Bokeh Effect Transformation Challenge. © 2023 IEEE.

关键词： Color photography

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A novel method for the construction of evolutionary tree based on expectation maximization algorithm

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Journal of Computational and Theoretical Nanoscience 2016年第6期13卷 3799-3803页

作者： Chen, Zhihua Zhao, Yang Wang, Zhuo Kou, Zheng Li, Hanggao Key Lab. of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan Hubei430074 China Institute of Biomedical and Pharmaceutical Sciences College of Biological Engineering and Food Science Hubei University of Technology Wuhan Hubei430068 China College of Computer Science South-Central University for Nationalities Wuhan Hubei430074 China

The difference of protein sequence or protein structure can be used for the construction of molecular evolutionary tree or phytogenetic tree with certain hierarchy and topology. The divergent points in the tree suggest that new genes appeared or common ancestors varied. The lengths of the branch in the tree show the evolution distances between proteins when divergences happened. The analysis of protein evolution can propose some methods for molecular evolution of various species and can confirm the accurate status in the evolution history. Moreover, the molecular evolution tree of proteins is a strong evidence for species classification. In the paper, the trees are constructed by the regular express of protein sequences and the expectation maximization (EM) algorithm. The proposed method in the paper can be used conveniently and can give reliable results, which benefit the biology computing and sequence analysis. Copyright © 2016 American Scientific Publishers. All rights reserved.

关键词： Proteins

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Collab.rative filtering algorithm via compressing the sparse user-rating-data matrix

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Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University 2009年第4期36卷 614-618+638页

作者： Hou, Cui-Qin Jiao, Li-Cheng Zhang, Wen-Ge Ministry of Education Key Lab. of Intelligent Perception and Image Understanding Research Inst. of Intelligent Information Processing Xidian Univ. Xi'an 710071 China

The paper proposes a novel memory-based collab.rative filtering algorithm-Multi-lab.l Probabilistic Latent Semantic Analysis based Collab.rative Filtering, which improves the quality of recommendations by reducing the dimension of the user-rating-data matrix by multi-lab.l probabilistic latent semantic analysis when the matrix is extremely sparse. Firstly, it confines the set of latent variables of probability latent semantic analysis to the set of multi-lab.l of items to make latent variables have meanings of corresponding lab.ls. Then it learns the probabilistic distribution of latent variables, i.e., the model of use's interest, to compress the user-rating-data matrix. Finally, it computes the similarity between different users based on the above learned model and makes recommendations. Compared to memory-based collab.rative filtering algorithms, the proposed algorithm decreases the mean absolute error 4 percents averagely on test dataset by reducing the dimension of the user-rating-data matrix. The proposed algorithm makes the recommendation system understandable and obtains competitive recommendations compared to the filtering algorithm which reduces the dimension of the user-rating-data matrix by probabilistic latent semantic analysis.

关键词： Iterative methods

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Reliability assessments of Chinese high speed railway network

Reliability assessments of Chinese high speed railway networ...

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2011 IEEE International Conference on Service Operations, Logistics and Informatics, SOLI 2011

作者： Zhang, Jianhua Hong, Liu Wang, Shuliang Xu, Xiaoming Department of Control Science and Engineering Key Lab for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China University of Shanghai for Science and Technology Shanghai Academy of System Science Shanghai 200093 China

ISBN: (纸本)9781457705731

With the economic developments, high speed railway has been paid many attentions in China and medium- short term planning of Chinese high speed railway network has been formed and most of the railways have been started into operations. In this paper, graph theory and complex network theory are adopted to assess the reliability of Chinese high speed railway network. The topological characteristics and real distances between pairs of stations are discussed to investigate the reliability of Chinese high-speed rail network. Several parameters are presented to investigate the topological characteristics and the reliability and robustness of the network subject to failures. The parameter called unit degree betweenness is proposed to assess the transport capacity of lines connecting with the nodes. The largest degree node-based attacks and the highest betweenness node-based attacks are involved into Chinese high speed railway network to assess the topological reliability and robustness. The results show that the highest betweenness node-based attacks are more effective to destroy the network than the largest degree node-based attacks. Moreover, the cumulative degree distribution and the real mileages of railways between pairs of stations can be fitted by Gauss functions, and the distribution of real shortest distances over all pairs of stations of the network is fitted by a normal distribution function. By the simulations, the critical stations, Guangzhou Station, Zhengzhou Station and Jinan Station for the largest degree node-based attacks, and Wuhan Station, Xuzhou Station and Shijiazhuang Station for the highest betweenness node-based attacks, can be obtained in this paper. © 2011 IEEE.

关键词： Graph theory

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A Hierarchical Optimizing Energy Management Strategy for Alleviating Degradation in Fuel Cell Hybrid System

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IEEE ACCESS 2024年 12卷 57117-57127页

作者： Fu, Jun Xiang, Qian Zeng, Linghong Zu, Yanmin You, Hang Shan, Xinkai Xin, Jie Li, Xi Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Processing & Intelligent Control Minist Educ Wuhan 430074 Peoples R China State Grid Corp China Beijing 102200 Peoples R China Hangzhou ArcSoft Software Co Ltd Hangzhou 310051 Peoples R China

This study designs an energy management strategy for fuel cell hybrid vehicles aimed to alleviating the performance degradation of Proton Exchange Membrane Fuel Cells (PEMFC), fuel consumption, and battery State of Charge (SOC) fluctuations during vehicle operation. The research focuses on the decrease in Electrochemical Surface Area (ECSA) due to Platinum (Pt) catalyst degradation, which is a key factor influencing PEMFC durability. An ECSA model based on the Pt dissolution mechanism is established, and a dynamic condition accelerated stress test (DC-AST) is designed to specifically investigate the impacts of key parameters, such as cycle period, amplitude, and duty cycle on the degradation of ECSA. This reveals the association between ECSA degradation and irregular potential fluctuations. A hierarchical power allocation strategy is then proposed, combining the global search capabilities of optimization algorithms with heuristic strategies in light of these features. The upper level employs Pontryagin's Minimum Principle (PMP) strategy for global power allocation optimization, while the lower level uses a satisfaction-based heuristic strategy that is tailored to the ECSA degradation characteristics, to dynamically adjust power output. Simulation results demonstrate that, compared to traditional rule-based strategies and classical PMP-based strategies, the proposed energy management strategy more effectively mitigates ECSA degradation of PEMFC under typical vehicle conditions.

关键词： Degradation Fuel cells Platinum Batteries Electric potential State of charge Resource management Hybrid power systems Energy management PEMFC hybrid power degradation ECSA energy management

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A probability-based object tracking method

A probability-based object tracking method

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4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013

作者： Song, Xu Li, Guoqiang Li, Ying Zhang, Yanning Shaanxi Province Key Lab. of Speech and Image Information Processing Northwestern Polytechnical University Xi'an 710129 China Science and Technology on Electro-optic Control Laboratory Louyang 471009 China

ISBN: (纸本)9783642420566

Here we take advantage of the signal recovery power of Compressive Sensing (CS) to significantly reduce the computational complexity brought by the high-dimension image data, then an effective and efficient low-dimensional subspace representation of the object is computing by applying Principal Component Analysis (PCA) to a collection of object observations which are low-dimensional vectors derived from CS. An incremental PCA algorithm is used to update this subspace model for characterizing the object appearance changes. Meanwhile, two distances derived from Probabilistic Principal Component Analysis (PPCA): distance from feature space (DFFS) and distance in feature space (DIFS), are used to describe visual similarity between the learned subspace representation model and candidate targets. Comparing with the traditional used reconstruction error, the sum of two distances: DFFS + DIFS, is more accurate and more robust to noises and partial occlusions. Numerous experiment demonstrate that subspace representation model can handle the situation that target objects experience pose changes, scale changes, significant illumination variation, partial occlusions and so on. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Compressed sensing

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DIRECTIONAL CLASSIFICATION OF CORTICAL SIGNALS USING A LIQUID STATE MACHINE

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IFAC Proceedings Volumes 2008年第2期41卷 9596-9600页

作者： Jiangshuai Huang Huijuan Fang Yongji Wang Key Lab. for Image Processing & Intelligent Control of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

Liquid State Machine (LSM) is a newly developed computational model with many interesting properties. It has great advantages of dealing with biologic computing when compared to the traditional computational model. In this paper, the LSM was used to deal with the direction classification problem of the spike series which were distilled from the neurons in motor cortex of a monkey. In the output layer, a linear regression and back-propagation are employed as the training algorithms. Compare to outcomes of the two algorithms, it is showed that ideal classification results were derived when using BP as the training algorithm.

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Parameter design method of stator flux estimation for direct torque control using ADRC

Parameter design method of stator flux estimation for direct...

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2nd IEEE Conference on Industrial Electronics and Applications (ICIEA 2007)

作者： Hu, Chanjuan Wani, Yubin Jiang, Xianglong Luo, Hui Deng, Guozhang Qin, Yi Wan, Shuyun Huazhong Univ Sci & Technol Dept Control Sci & Engn Wuhan 430074 Hubei Peoples R China Key Lab Image Processing & Intelligent Control Wuhan 430074 Peoples R China HuangGang Politech Coll Wuhan 430074 Peoples R China

ISBN: (纸本)9781424407361

In traditional Direct Torque control (DTC), speed regulator is widely based on conventional Proportional Integral Derivative (PID) controller, which has to depend on precise math model of the subject. However, PID cannot easily achieve swift response, small overshooting and fine speed control precision especially in low speed range. This paper introduces a nonlinear control tcchnology-Auto Disturbance Rejection controller (ADRC) into DTC to improve the speed adaptation capability and robustness, and a parameter design method of stator flux estimation is proposed. The simulation results prove the system has good control performance.

关键词： Torque control

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An improved method in change detection of multitemporal remote sensing image

An improved method in change detection of multitemporal remo...

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4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013

作者： Liao, Fangshun Yu, Sufen Li, Ying Zhang, Yanning Shaanxi Provincial Key Lab. of Speech and Image Information Processing Northwestern Polytechnical University Xi'an Shaanxi 710072 China Science and Technology on Electro-optic Control Laboratory Louyang 471009 China

ISBN: (纸本)9783642420566

Traditional Markov random Field (MRF) methods assume that neighboring pixels tend to have the same lab.l. However, this assumption is always inconsistent with the actual situation and affects the resultant accuracy of the algorithm. To overcome this, we propose an object-based Markov Random Field (OMRF) model and a change detection method based on OMRF model. The OMRF model assumes that pixels within same object are in the same class. First, we generate the difference image from multi-temporal remote sensing images. Second, Mean Shift is applied to extract objects from difference image. Finally, change detection map is generated by iterative algorithm. The experimental results show that the algorithm can effectively improve the detection accuracy of the algorithm on real remote sensing datasets. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Change detection

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Hessian based image structure adaptive gradient vector flow for parametric active contours

Hessian based image structure adaptive gradient vector flow ...

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2010 17th IEEE International Conference on image processing, ICIP 2010

作者： Wang, Y.Q. Chen, W.F. Yu, T.L. Zhang, Y.T. Tianjin Key Lab. of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin 300191 China Key Lab. of Image Processing Southern Medical University Guangzhou 510515 China Dept. of Radiology General Hospital Tianjin Medical University Tianjin 300052 China

ISBN: (纸本)9781424479948

Active contours have been one of the most successful methods for image segmentation during the last two decades, but one of the shortcomings of being unable to converge to concavity is a handicap to its effectiveness. In order to address this issue, the gradient vector flow (GVF) was put forth. Although there have been a great number of works on GVF, the image structure has seldom been incorporated into GVF algorithm. In this work, the image structure characterized by the Hessian matrix is incorporated into the GVF algorithm by reformulating the smoothness constraint of GVF into matrix form. In this way, the associated diffusion PDEs are anisotropic and the modified GVF snake can converge to very long concavity and preserve weak edge simultaneously. Experiments and comparisons are presented to demonstrate the properties of the proposed strategies. © 2010 IEEE.

关键词： image segmentation

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