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International Conference on Intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Jiaoying Jin Mingyue Ding Xin Yang Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Life School of Science and Technology Huazhong University of Science and Technology Wuhan China State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence(IPRAI) Life School of Science and Technology Huazhong University of Science and Technology Wuhan China

The analysis of the carotid artery wall is of paramount importance in clinical practice. Especially, the intima-media thickness is a risk index for some of the most severe acute cerebrovascular pathologies, hence, an accurate segmentation of the different layers of the carotid artery is needed. IMT is usually manually measured on longitudinal B-mode ultrasound images. In the past ten years, many computer-based techniques for intima-media thickness measurement have been proposed to overcome the limits of manual segmentation, but almost all of them require a certain degree of user interaction. In this paper we proposed a novel approach for the completely user-independent segmentation of the common carotid artery wall. Our algorithm is designed for the extraction of the intima and media layers of the distal carotid wall in ultrasound images. It is based on integrated approach consisting of common carotid artery region identification, contour initialization with threshold segmentation, intima-lumen segmentation with Snake, and media-adventitia segmentation with GVF-Snake that enables the automated tracing of the carotid walls. The acoustic impedance's difference is employed to locate common carotid artery region. Finally, the characterization of the algorithm in terms of segmentation error was evaluated with a set of 40 common carotid artery ultrasound images and compared to the segmentation traced by a trained operator. Experiments showed that a mean error lower than 1.3 pixel both on the intima and media layers was obtained, which is comparable to that obtained by means of operator dependent techniques.

关键词： image segmentation Carotid arteries Ultrasonic imaging Media Algorithm design and analysis Ultrasonic variables measurement

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Data-Driven Discovery of Stochastic Differential Equations

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Engineering 2022年第10期17卷 244-252页

作者： Yasen Wang Huazhen Fang Junyang Jin Guijun Ma Xin He Xing Dai Zuogong Yue Cheng Cheng Hai-Tao Zhang Donglin Pu Dongrui Wu Ye Yuan Jorge Gonçalves Jürgen Kurths Han Ding School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Department of Mechanical Engineering University of KansasLawrenceKS 66045USA HUST-Wuxi Research Institute Wuxi 214174China Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Department of Plant Sciences University of CambridgeCambridge CB23EAUK Luxembourg Centre for Systems Biomedicine University of LuxembourgBelvaux 4367Luxembourg Department of Physics Humboldt University of BerlinBerlin 12489Germany Department of Complexity Science Potsdam Institute for Climate Impact ResearchPotsdam 14473Germany

Stochastic differential equations(SDEs)are mathematical models that are widely used to describe complex processes or phenomena perturbed by random noise from different *** identification of SDEs governing a system is often a challenge because of the inherent strong stochasticity of data and the complexity of the system’s *** practical utility of existing parametric approaches for identifying SDEs is usually limited by insufficient data *** study presents a novel framework for identifying SDEs by leveraging the sparse Bayesian learning(SBL)technique to search for a parsimonious,yet physically necessary representation from the space of candidate basis *** importantly,we use the analytical tractability of SBL to develop an efficient way to formulate the linear regression problem for the discovery of SDEs that requires considerably less time-series *** effectiveness of the proposed framework is demonstrated using real data on stock and oil prices,bearing variation,and wind speed,as well as simulated data on well-known stochastic dynamical systems,including the generalized Wiener process and Langevin *** framework aims to assist specialists in extracting stochastic mathematical models from random phenomena in the natural sciences,economics,and engineering fields for analysis,prediction,and decision making.

关键词： Data-driven method System identification Sparse Bayesian learning Stochastic differential equations Random phenomena

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Convergence analysis of nonconvex distributed stochastic zeroth-order coordinate method

arXiv

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arXiv 2021年

作者： Zhang, Shengjun Dong, Yunlong Xie, Dong Yao, Lisha Bailey, Colleen P. Fu, Shengli OSCAR Laboratory Department of Electrical Engineering University of North Texas DentonTX76207 United States School of Artificial Intelligence and Automation The MOE Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China

This paper investigates the stochastic distributed nonconvex optimization problem of minimizing a global cost function formed by the summation of n local cost functions. We solve such a problem by involving zeroth-order (ZO) information exchange. In this paper, we propose a ZO distributed primal–dual coordinate method (ZODIAC) to solve the stochastic optimization problem. Agents approximate their own local stochastic ZO oracle along with coordinates with an adaptive smoothing parameter. We show that the proposed algorithm achieves the convergence rate of O(√p/√T) for general nonconvex cost functions. We demonstrate the efficiency of proposed algorithms through a numerical example in comparison with the existing state-of-the-art centralized and distributed ZO algorithms. Copyright © 2021, The Authors. All rights reserved.

关键词： Stochastic systems

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A nonlinear sliding mode observer for the estimation of temperature distribution in the planar solid oxide fuel cell stack

A nonlinear sliding mode observer for the estimation of temp...

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第五届世界氢能技术大会(WHTC2013)

作者： Huan Cheng Xi Li Jianhua Jiang Lin Zhang Jian Li Jie Yang Department of control science and Engineering Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China School of Materials Science and Engineering State Key Laboratory of Material Processing and Die and Mould Technology Huazhong University of Science and Technology Wuhan 430074 China School of Mechanical and Electronic Information China University of Geosciences Wuhan 430074 China

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Indirect effects among biodiversity loss of mutualistic ecosystems

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National Science Open 2022年第2期1卷 8-18页

作者： Guangwei Wang Xueming Liu Guanrong Chen Hai-Tao Zhang School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent ControlHuazhong University of Science and TechnologyWuhan 430074China State Key Lab of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Department of Electrical Engineering City University of Hong KongHong KongChina

Drastic reduction in biodiversity has been a severe threat to ecosystems,which is exacerbated when losing few species leads to disastrous and even irreparable ***,revealing the mechanism underlying biodiversity loss is of uttermost *** this study,we show that abundant indirect interactions among mutualistic ecosystems are critical in determining species’*** topological and ecological characteristics,we propose an indicator derived from a dynamic model to identify keystone species and quantify their influence,which outperforms widely-used indicators like degree in realistic and simulated ***,we demonstrate that networks with high modularity,heterogeneity,biodiversity,and less intimate interactions tend to have larger indirect effects,which are more amenable in predicting decline of biodiversity with the proposed *** findings shed some light onto the influence of apposite biodiversities,paving the way from complex network theory to ecosystem protection and restoration.

关键词： biodiversity indirect effect complex network mutualism

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Nonconvex penalties with analytical solutions for one-bit compressive sensing

arXiv

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arXiv 2017年

作者： Huang, Xiaolin Yan, Ming Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University MOE Key Laboratory of System Control and Information Processing Shanghai200240 China Department of Computational Mathematics Science and Engineering Department of Mathematics Michigan State University East LansingMI48824 United States

One-bit measurements widely exist in the real world and can be used to recover sparse signals. This task is known as one-bit compressive sensing (1bit-CS). In this paper, we propose novel algorithms based on both convex and nonconvex sparsity-inducing penalties for robust 1bit-CS. We consider the dual problem, which has only one variable and provides a sufficient condition to verify whether a solution is globally optimal or not. For positive homogeneous penalties, a globally optimal solution can be obtained in two steps: a proximal operator and a normalization step. For other penalties, we solve the dual problem, and it needs to evaluate the proximal operators for many times. Then we provide fast algorithms for finding analytical solutions for three penalties: minimax concave penalty (MCP), 0norm, and sorted 1penalty. Specifically, our algorithm is more than 200 times faster than the existing algorithm for MCP. Its efficiency is comparable to the algorithm for the 1penalty in time, while its performance is much better than 1. Among these penalties, sorted 1is most robust to noise in different settings. Copyright © 2017, The Authors. All rights reserved.

关键词： Compressed sensing

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Robust Perturbed Output Regulation and Its Application to Synchronization of Nonlinear Heterogeneous Multi-Agents

Robust Perturbed Output Regulation and Its Application to Sy...

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IEEE Annual Conference on Decision and control

作者： Xi Chen Zhiyong Chen Hai-Tao Zhang School of Electrical Engineering and Computer Science The University of Newcastle Callaghan NSW 2308 Australia Key Laboratory of Image Processing and Intelligent Control School of Automation and the State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan 430074 P.R. China

ISBN: (纸本)9781467360890

The conventional output regulation problem aims to achieve reference tracking and disturbance rejection while references and disturbances are generated by an autonomous exosystem. When the exosystem is perturbed by an external event, a novel robust perturbed output regulation problem is formulated and solved in this paper. The formulation arises from a kind of synchronization problem of multiple agents. Hence, the proposed solution leads to a decentralized control algorithm for synchronization of multiple agents with nonlinear heterogeneous dynamics.

关键词： Output Regulation decentralized control algorithm Disturbance rejection external events Computer algorithms

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Convergence Analysis of Nonconvex Distributed Stochastic Zeroth-order Coordinate Method

Convergence Analysis of Nonconvex Distributed Stochastic Zer...

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IEEE Conference on Decision and control

作者： Shengjun Zhang Yunlong Dong Dong Xie Lisha Yao Colleen P. Bailey Shengli Fu OS-CAR Laboratory University of North Texas Denton TX USA School of Artificial Intelligence and Automation the MOE Key Laboratory of Image Processing and Intelligent Control and the State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan China University of North Texas Denton TX USA

ISBN: (纸本)9781665436601

This paper investigates the stochastic distributed nonconvex optimization problem of minimizing a global cost function formed by the summation of n local cost functions. We solve such a problem by involving zeroth-order (ZO) information exchange. In this paper, we propose a ZO distributed primal–dual coordinate method (ZODIAC) to solve the stochastic optimization problem. Agents approximate their own local stochastic ZO oracle along with coordinates under an adaptive smoothing parameter. We show that the proposed algorithm achieves the convergence rate of ${\mathcal{O}}(\sqrt p /\sqrt T )$ for general nonconvex cost functions. We demonstrate the efficiency of proposed algorithms through a numerical example in comparison with the existing state-of-the-art centralized and distributed ZO algorithms.

关键词： Smoothing methods Conferences Benchmark testing Cost function Approximation algorithms Information exchange Convergence

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Modified lifting algorithm and VLSI architecture for the 9/7 wavelet filters

Modified lifting algorithm and VLSI architecture for the 9/7...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Chen-Gyi Xiong Zhi-Rong Gao Jin-Wen Tian Jian Liu The State Key Laboratory of Education Commission for Image Processing and Intelligent Control Institute of Pattern Recognition & Artificial Intelligence Huazhong University of Science and Technology Wuhan China Department of Computer Science Wuhan University of Science and Engineering Hebei China

ISBN: (纸本)0780384032

A new parallel-based lifting algorithm (PBLA) for the 9/7 filters, exploring the parallelism of arithmetic operations in each lifting step, was proposed in this paper. It shortened significantly the critical path of computation, and resulted in a fast VLSI implementation architecture. In comparison with the conventional lifting algorithm based implementation (CLABI), the latency is reduced by more than half from (4T/sub m/ + 8T/sub a/) to (T/sub m/ + 4T/sub a/), which is competitive to that of convolution based implementation CBI, and can be further reduced to Tm by inserting 3 stages of pipeline. The experimental results demonstrate that the proposed architecture has good performances in both speed and area.

关键词： Very large scale integration Discrete wavelet transforms Filters image coding Delay Parallel processing Arithmetic Convolution Hardware Transform coding

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Implicit Ray-Transformers for Multi-view Remote Sensing image Segmentation

arXiv

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arXiv 2023年

作者： Qi, Zipeng Chen, Hao Liu, Chenyang Shi, Zhenwei Zou, Zhengxia The Image Processing Center School of Astronautics The Beijing Key Laboratory of Digital Media The State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China The Shanghai Artificial Intelligence Laboratory Shanghai200232 China The Department of Guidance Navigation and Control School of Astronautics Beihang University Beijing100191 China

The mainstream CNN-based remote sensing (RS) image semantic segmentation approaches typically rely on massive labeled training data. Such a paradigm struggles with the problem of RS multi-view scene segmentation with limited labeled views due to the lack of considering 3D information within the scene. In this paper, we propose "Implicit Ray-Transformer (IRT)" based on Implicit Neural Representation (INR), for RS scene semantic segmentation with sparse labels (such as 4-6 labels per 100 images). We explore a new way of introducing multi-view 3D structure priors to the task for accurate and view-consistent semantic segmentation. The proposed method includes a two-stage learning process. In the first stage, we optimize a neural field to encode the color and 3D structure of the remote sensing scene based on multi-view images. In the second stage, we design a Ray Transformer to leverage the relations between the neural field 3D features and 2D texture features for learning better semantic representations. Different from previous methods that only consider 3D prior or 2D features, we incorporate additional 2D texture information and 3D prior by broadcasting CNN features to different point features along the sampled ray. To verify the effectiveness of the proposed method, we construct a challenging dataset containing six synthetic sub-datasets collected from the Carla platform and three real sub-datasets from Google Maps. Experiments show that the proposed method outperforms the CNN-based methods and the state-of-the-art INR-based segmentation methods in quantitative and qualitative metrics. Ablation study shows that under limited label conditions, the combination of the 3D structure prior and 2D texture can significantly improve the performance and effectively complete missing semantic information in novel views. Experiments also demonstrate the proposed method could yield geometry-consistent segmentation results against illumination changes and viewpoint changes. Our dat

关键词： Remote sensing

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