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International Conference on Information Engineering and Computer Science (ICIECS)

作者： Jianglin Ma Zhouwei Zhang Chengyi Wang Zhong Chen Remote Sensing Image Processing Laboratory Institute of Remote Sensing Applications Chinese Academy and Sciences Beijing China Institute for Pattern Recognition & Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424449934

A classifier-based method to select and fuse grey level co-occurrence matrix (GLCM), Gaussian Markov random field (GMRF) and discrete wavelet transform (DWT) features to improve texture discrimination is presented. Feature selection via wrapper approaches is applied to find the optimal combination of texture features. The fused features have obtained higher discrimination accuracy compared with individual features. The curse of dimensionality is shown to affect discrimination accuracy, and feature selection and reduction helps obtain higher accuracy. Overall our proposed classifier-based method obtains the highest discrimination accuracy compared to other feature reduction methods such as principal component analysis (PCA) and linear discriminant analysis (LDA). Meanwhile GLCM features are found to produce higher discrimination accuracy than GMRF and DWT, and LDA is demonstrated to obtain higher discrimination accuracy than PCA.

关键词： Discrete wavelet transforms Linear discriminant analysis Signal processing algorithms Feature extraction Remote sensing Markov random fields Principal component analysis Classification algorithms Fuses Wavelet analysis

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An Active Landing Recovery Method for Quadrotor UAV: Localization, Tracking and Buffering Landing

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IFAC-PapersOnLine 2023年第2期56卷 3366-3372页

作者： Yongkang Xu Zhihua Chen Shoukun Wang Junzheng Wang National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Beijing CO 100081 P.R.China Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition and MOE Key Lab of Nondestructive Testing Technology School of Information Engineering Nanchang Hangkong University Nanchang CO 330063 P.R. China

This paper proposes a principle of fully autonomous ground mobile landing recovery of Unmanned Aerial Vehicles (UAV) for the problems of relatively fixed landing point, passive recovery, poor flexibility, and environmental adaptability, which mainly includes localization, landing point tracking, and buffering landing for quadrotor UAV. Firstly, aiming at the problem that it is difficult to accurately obtain the position of a UAV in dynamic mobile landing recovery, a target location method based on Asynchronous Multisensor Information Fusion(AMIF) and servo turntable focus tracking is proposed. Secondly, to achieve fast and high-precision tracking of UAVs, a tracking control strategy of an independently driven landing recovery system and a Stewart six-degree of freedom platform is proposed. Then, to solve the problems of large impact force and center of gravity instability in the landing process of UAV, a stationarity control algorithm based on model prediction and a compliance control algorithm based on adaptive variable impedance are designed to achieve active compliance control while adjusting the position and attitude of the receiving surface in real-time. Finally, a quadrotor unmanned landing and recovery experimental platform is built to verify the feasibility of the ground mobile landing and recovery strategy proposed in this paper and the effectiveness of the control algorithm.

关键词： Quadrotor UAV Mobile Autonomous recovery Target localization Falling point tracking Buffering landing

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Ultrasound Carotid Artery Intima-Media Thickness (IMT) Segmentation Review

Ultrasound Carotid Artery Intima-Media Thickness (IMT) Segme...

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

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

Stroke and heart attack, which could be led by a kind of cerebrovascular and cardiovascular disease named asatherosclerosis, would seriously cause human morbidity and mortality. And the carotid artery of intima-media thickness (IMT) is a key indicator to the disease. With the development of computer assisted diagnosis (CAD) technology, Ultrasound imaging, being real-time, economic, reliable, safe, and now seems to become a standard in vascular assessment methodology especially for the measurement of IMT. This review is an attempt to discuss the clinical relevance of measurements in clinical practice at first, and then followed by the challenges that one has to face when approaching the segmentation of ultrasound images. Secondly, the paper is presentation of common used methods for the IMT segmentation and measurement. An overview of summary and future perspectives is given in conclusion finally.

关键词： Ultrasonic imaging image segmentation Carotid arteries Ultrasonic variables measurement Biomedical imaging

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A hybrid method to segment common carotid arteries from 3D ultrasound images

A hybrid method to segment common carotid arteries from 3D u...

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IEEE EMBS International Conference on Information Technology Applications in Biomedicine (ITAB)

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

A hybrid method is used to evaluate atherosclerosis through a mathematical morphology approach and GVF-Snake method. Common carotid artery (CCA) segmentation requires outlining the intima and adventitia contours on the transverse view of B-mode ultrasound (US) images. The lumen and adventitia contours are segmented using a morphology and GVF-Snake methods, respectively. Upon analyzing ten separate patient data sets demonstrate that a comparison between the proposed method and the traditional approach (manual contouring) on 110 transverse images of the CCA showed a mean absolute distance (MAD) of 0.67±0.17mm for lumen and 0.64 ± 0.19mm for adventitia. Their Dice Similarity Coefficient (DSC) values are 92.7%±2.3% and 90.3%±3.5% for lumen and adventitia segmentation, respectively. These values are in good agreement with clinical standards.

关键词： image segmentation Three dimensional displays Measurement Biomedical imaging Ultrasonic imaging Sun

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Research on Large-Scale Scene Infrared Simulation Based on image Classification

Research on Large-Scale Scene Infrared Simulation Based on I...

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International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Lamei Zou Tianxu Zhang Wei Lv Guoqing Ao Institute of Pattern Recognition and Artificial Intelligence National key laboratory of science and technology on multi-spectral information processing technologies Huazhong University of Science and Technology Wuhan China

Vega has been widely used in Virtual Reality (VR) field. Vega infrared (IR) module can implement IR simulation, but Vega IR imaging simulation's general approach does not apply to large-scale scene's infrared simulation problem. This article deeps into large-scale scene IR image simulation through Vega infrared module based on visible image, the scene's corresponding Digital Elevation Model (DEM) data and targets' 3D model. A real time large-scale IR simulation system is successfully designed and realized in this paper. At the aspect of image classification, a coarse to fine k-means clustering method based on the consistency of image color is proposed. The proposed automatic texture material mapping method based on the development of Vega TMM tool provides a fast and convenient way for large-scale scene's IR simulation based on Vega IR module. And finally, results of the large-scale scene infrared simulation show the effectiveness of this method.

关键词： Solid modeling image color analysis Materials Atmospheric modeling image classification Three dimensional displays Pixel

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Automatic Detection of the Intima-Media Layer in Ultrasound Common Carotid Artery image Based on Active Contour Model

Automatic Detection of the Intima-Media Layer in Ultrasound ...

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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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Cooperative path planning for multiple air vehicles using a co-evolutionary algorithm

Cooperative path planning for multiple air vehicles using a ...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Chang-Wen Zheng Ming-Yue Ding Cheng-Ping Zhou State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattem Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

The coordinated path-planning problem for multiple unmanned air vehicles is studied with the proposal of a co-evolving and cooperating path planner. In the new planner, potential paths of each vehicle form their own subpopulation, and evolve only in their own sub-population, while the interaction among all sub-problems is reflected by the definition of fitness function. Meanwhile, the individual candidates are evaluated with respect to the workspace so that the computation of the configuration space is avoided. By using a problem-specific representation of candidate solutions and genetic operators, our algorithm can take into account different kinds of mission constraints and generate the solutions in real-time.

关键词： Path planning Unmanned aerial vehicles Level measurement Terrain mapping Genetics Evolutionary computation Laboratories image processing Intelligent control image recognition

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RBP-Former: Joint Prediction of RNA-protein Binding Sites on Full-length RNA Transcripts for Multiple RBPs

RBP-Former: Joint Prediction of RNA-protein Binding Sites on...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yichong Li Xiaojian Liu Fan Cheng Xiaoyong Pan Yang Yang Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

RNA-binding proteins (RBPs) are essential for gene expression, and the complex RNA-protein interaction mechanisms require analysis of global RNA information. Therefore, accurate prediction of RBP binding sites on full-length RNA transcripts is crucial for understanding these mechanisms and their roles in diseases. While machine learning methods can predict RBP binding to RNA fragments, extending this to full-length transcripts presents challenges due to sequence length and data imbalance. In this paper, we introduce RBP-Former, a binding site joint prediction model designed specifically for full-length RNA transcripts that can be used for multiple RBPs. This model processes information at both coarse and fine-grained levels to fully exploit sequence data and its interactions with multiple RBPs. We develop multi-level imbalance learning strategies, achieving favorable results on imbalanced data. Our method outperforms existing methods in predicting binding sites on full-length RNA transcripts for multiple RBPs, demonstrating its effectiveness in handling imbalanced label and sample distributions.

关键词： Proteins Protein engineering Accuracy RNA Machine learning Predictive models Data models Gene expression Bioinformatics Diseases

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Moving object segmentation based on new likelihood functions

Moving object segmentation based on new likelihood functions

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IEEE International Symposium on Intelligent Signal processing and Communication Systems (ISPACS)

作者： Xiang Zhang Zhi Liu Jie Yang Institute of Image Processing and Patter Recognition Shanghai Jiaotong University China Key Laboratory of Advanced Display and System Application Ministry of Education Shanghai University China

Accurate segmentation of moving objects from a video sequence is still a difficult task. A moving object segmentation method is proposed in this paper to deal with the segmentation splits and defects. First, it is claimed that the confusion point is one reason for the segmentation inaccuracy, and corresponding solution is also presented. According to the solution, new likelihood functions are proposed to compute membership probabilities, which are then used for final segmentation within an energy minimization framework. Unlike related algorithms which compute membership probabilities using kernel density estimation, the proposed method models the membership probabilities as functions with kernel density estimation as the independent variable. Experiments show that improved results are generated by the proposed likelihood functions.

关键词： Radio access networks

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Optimized hidden markov model based on constrained particle swarm optimization

arXiv

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arXiv 2018年

作者： Chang, Liu Ouzrout, Yacine Nongaillard, Antoine Bouras, Abdelaziz Jiliu, Zhou DISP Laboratory University Lumiere of Lyon 2 France Key Laboratory of Pattern Recognition and Intelligent Information Processing in Sichuan China College of Information Science and Technology Chengdu University Chengdu China

As one of Bayesian analysis tools, Hidden Markov Model (HMM) has been used to in extensive applications. Most HMMs are solved by Baum-Welch algorithm (BWHMM) to predict the model parameters, which is difficult to find global optimal solutions. This paper proposes an optimized Hidden Markov Model with Particle Swarm Optimization (PSO) algorithm and so is called PSOHMM. In order to overcome the statistical constraints in HMM, the paper develops re-normalization and re-mapping mechanisms to ensure the constraints in HMM. The experiments have shown that PSOHMM can search better solution than BWHMM, and has faster convergence speed. Copyright © 2018, The Authors. All rights reserved.

关键词： Hidden Markov models

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