检索结果-内蒙古大学图书馆

2021 CIE International Conference on Radar, Radar 2021

作者： Li, Xianghai Yang, Zhiwei He, Shun Tan, Xiao Liao, Guisheng Xidian University National Laboratory of Radar Signal Processing Xi'an China Xi'An University of Science and Technology Communication and Information Engineering College Xi'an China

ISBN: (纸本)9781665498142

In multi-satellite formation synthetic aperture radar (SAR) systems, terrain interferometric phase is a crucial factor that degrades the performance of multi-channels coherence processing. To address this issue, we developed a high-precision self-adaptive topographic phase compensation (TPC) method. It emphasizes minimizing the topographic phase estimation error based on an error feedback weighting correction structure. The self-adaptive weighting coefficient is constructed using image coherence, phase residual distribution, and fringe structural features. This ensures that the phase estimation error component will be corrected in an extremely heterogeneous observation scene. The experimental results of multi-satellite SAR image simulated data demonstrate that the proposed method can significantly improve the accuracy of the topographic phase compensation. © 2021 IEEE.

关键词： error feedback weighting correction fringe structural features rough-and-refined estimation Topographic phase compensation

来源：评论

学校读者我要写书评

暂无评论

Three-dimensional imaging using the electromagnetic vortex synthetic aperture radar

Three-dimensional imaging using the electromagnetic vortex s...

引用

2021 CIE International Conference on Radar, Radar 2021

作者： Lv, Kun Zhu, Guangyu Ma, Hui Liu, Hongwei Shao, Shuai Wei, Jiaqi Xidian University National Laboratory of Radar Signal Processing Xi'an710071 China School of Information Science and Technology Northwest University Xi'an710069 China

ISBN: (纸本)9781665498142

The electromagnetic vortex (EMV) wave is so called for carrying the orbital angular momentum (OAM). It introduces the diversity in not only the along track propagation, but also in the wavefront plane. Combining the EMV wave with the traditional synthetic aperture imaging (SAR), this paper proposes a novel 3D imaging scheme, namely the EMV-SAR. First, the SAR echo is extended into 3D after involving the OAM mode domain. The 2D instantaneous information is thus obtained by one single pulse, not only the range information, and also the azimuth by simply applying Fourier transform to the OAM mode domain. Then a joint two-dimensional azimuthal compression algorithm is proposed for generating the 3D target imaging. The simulation results have validated the performance of the proposed system and algorithms, and demonstrated the superiority of the EMV-SAR for the 3D radar imaging. © 2021 IEEE.

关键词： 3D radar imaging Electromagnetic vortex wave joint two-dimensional azimuth compression orbital angular momentum

来源：评论

学校读者我要写书评

暂无评论

Exploring Multimodal Sentiment Analysis via CBAM Attention and Double-layer BiLSTM Architecture

arXiv

引用

arXiv 2023年

作者： Wang, Huiru Li, Xiuhong Ren, Zenyu Yang, Dan Ma, Chunming Xinjiang Key Laboratory of Signal Detection and Processing College of Information Science and Engineering Xinjiang University Urumqi China Xinjiang Multilingual Information Technology Laboratory College of Information Science and Engineering Xinjiang University Urumqi China

Because multimodal data contains more modal information, multimodal sentiment analysis has become a recent research hotspot. However, redundant information is easily involved in feature fusion after feature extraction, which has a certain impact on the feature representation after fusion. Therefore, in this papaer, we propose a new multimodal sentiment analysis model. In our model, we use BERT + BiLSTM as new feature extractor to capture the long-distance dependencies in sentences and consider the position information of input sequences to obtain richer text features. To remove redundant information and make the network pay more attention to the correlation between image and text features, CNN and CBAM attention are added after splicing text features and picture features, to improve the feature representation ability. On the MVSA-single dataset and HFM dataset, compared with the baseline model, the ACC of our model is improved by 1.78% and 1.91%, and the F1 value is enhanced by 3.09% and 2.0%, respectively. The experimental results show that our model achieves a sound effect, similar to the advanced model. Copyright © 2023, The Authors. All rights reserved.

关键词： Data fusion

来源：评论

学校读者我要写书评

暂无评论

Adaptive Gaussian Regularization Constrained Sparse Subspace Clustering for Image Segmentation

Adaptive Gaussian Regularization Constrained Sparse Subspace...

引用

International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Sensen Song Dayong Ren Zhenhong Jia Fei Shi School of Computer Science and Technology Xinjiang University Urumqi China Key Laboratory of Signal Detection and Processing Xinjiang Uygur Autonomous Region Urumqi China College of Mathematics and System Science Xinjiang University Urumqi China National Key Laboratory for Novel Software Technology Nanjing University Nanjing China

Sparse Subspace Clustering (SSC) is integral to image processing, drawing from spectral clustering foundations. However, prevalent methods, relying on an l 1 -norm constraint, fail to capture nuanced inter-region correlations, affecting segmentation efficacy. To remedy this, we introduce an Adaptive Gaussian Regularization Constrained SSC for enhanced image segmentation. This method begins with superpixel preprocessing to enrich local information. Given the Gaussian nature of the SSC’s sparse coefficient matrix, a Gaussian probability density function is infused as a regularization term, reinforcing regional image ties and facilitating similarity matrix creation. Using spectral clustering, we then define superpixel clusters leading to the final segmentation. When tested against the BSDS500 and SBD datasets and other leading algorithms, our model showcases marked improvements in natural image segmentation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Optimization of Coupled ARX-Laguerre Multimodel Parameters Using Genetic Algorithm

Optimization of Coupled ARX-Laguerre Multimodel Parameters U...

引用

International Conference on Systems and Control (ICSC)

作者： Hajer Benamor Marwa Yousfi Larbi Chrifi Alaoui Tarek Garna Laboratory of Automatic Signal and Image Processing (LARATSI) National Engineering School of Monastir Monastir Tunisia Laboratory of Innovative Technology (LTI UR-UPJV 3899) University of Picardie Jules Verne Amiens France Higher Institute of Applied Science and Technology of Sousse Sousse Tunisia

ISBN: (数字)9798331531812

ISBN: (纸本)9798331531829

This work treats parametric optimization of nonlinear systems using genetic algorithms. The authors focus, in this paper, in combining the ARX-Laguerre model and the multimodel approach with its coupled configuration to develop a model named the coupled ARX-Laguerre multimodel. The proposed model is characterized by its Laguerre poles, Fourier coefficients and weighting functions parameters. The complexity of the model is tightly related to the optimal identification of the Laguerre poles characterizing the model. The authors propose an optimization algorithm of the multimodel parameters (Laguerre poles and weighting functions parameters) based on the genetic to guarantee a significant parametric number reduction with regards to the classic ARX multimodel.

关键词： Uncertainty Solids Genetics Control systems Chemical reactions Iterative algorithms Complexity theory Nonlinear systems Optimization Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

A multi-target tracking algorithm based on Gaussian mixture model

引用

Journal of Systems Engineering and Electronics 2020年第3期31卷 482-487页

作者： SUN Lili CAO Yunhe WU Wenhua LIU Yutao National Laboratory of Radar Signal Processing Xidian UniversityXi’an 710071China Science and Technology on Communication Networks Laboratory Shijiazhuang 050081China

Since the joint probabilistic data association(JPDA)algorithm results in calculation explosion with the increasing number of targets,a multi-target tracking algorithm based on Gaussian mixture model(GMM)clustering is *** algorithm is used to cluster the measurements,and the association matrix between measurements and tracks is constructed by the posterior *** with the traditional data association algorithm,this algorithm has better tracking performance and less computational *** results demonstrate the effectiveness of the proposed algorithm.

关键词： multiple-target tracking Gaussian mixture model(GMM) data association expectation maximization(EM)algorithm

来源：评论

学校读者我要写书评

暂无评论

High Frame Rate Along-Track Swarm SAR Sub-Aperture Collaboration Imaging for Moving Target

引用

IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Jiang, Nan Chen, Jianlai Zhu, Jiahua Liang, Buge Yang, Degui Huang, Xiaotao Xing, Mengdao Central South University School of Automation Changsha410083 China National University of Defense Technology College of Meteorology and Oceanography Changsha410073 China National University of Defense Technology College of Electronic Science and Technology Changsha410073 China Xidian University National Laboratory of Radar Signal Processing Xi’an710071 China

As a novel configuration of along-track Multistatic SAR (Multi-SAR), the high frame rate Along-Track Swarm SAR (ATS-SAR) has garnered significant attention in recent years due to its exceptional efficiency in reducing data acquisition time. Motivated by its potential for high-resolution imaging of moving targets, this paper investigates the application of ATS-SAR in moving target imaging. However, high frame rate ATS-SAR-based moving target imaging confronts two critical challenges: time-space coupling and partial data loss in moving target echoes. To address these challenges, we first conduct a comprehensive analysis and theoretical derivation of the moving target echo model under the high frame rate ATS-SAR configuration. Subsequently, we propose an innovative motion parameter estimation algorithm that exploits unique echo characteristics to achieve high-performance imaging. Furthermore, we introduce the highresolution, high frame rate ATS-SAR Sub-Aperture Collaborative Imaging algorithm for Moving Targets (MT-SACIm-ATS). Extensive simulations and a real measured experiment validate the effectiveness of the MT-SACIm-ATS algorithm, demonstrating imaging performance that closely approximates reference imaging results. Comparative analysis with several state-of-the-art algorithms further highlights the superiority of the proposed approach in terms of resolution and robustness. © 1980-2012 IEEE.

关键词： Imaging Synthetic aperture radar Apertures Data acquisition Transmitters Radar polarimetry Radar imaging Parameter estimation High-resolution imaging Estimation

来源：评论

学校读者我要写书评

暂无评论

Optimized Statistical Model for Complex Chemical Processes Monitoring

Optimized Statistical Model for Complex Chemical Processes M...

引用

Data Driven Control and Learning Systems (DDCLS)

作者： Jian Zhang Xiaohe Qu Zhiwei Lei Haifeng Zhang Kai Zhong Datang East China Electric Power Test and Research Institute Hefei China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Mathematical Science Anhui University Hefei China Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education Institutes of Physical Science and Information Technology Anhui University Hefei Anhui China

The traditional kernel principal components analysis (KPCA) and linear discriminant analysis (LDA) have been verified to be two effective approaches for fault detection and diagnosis in recent years. Nevertheless, the conventional method and corresponding improved ones still exposed their deficiencies in some ways. Facing this dilemma, this paper presents a combination of optimized KPCA and modified LDA (OKPCA-MLDA), in which the OKPCA avoids the loss of original features after centralizing data in the eigenspace by adjusting covariance matrix's eigenvalue and transforming the distribution of variables thus providing representative and abundant principal components for the classifier. In addition, the MLDA maximizes a brand new objective function in feature space which achieves better classification performance than the conventional LDA, then utilizing diagnostic thresholds and similarity coefficients to identify the fault types. Based on the combined model, not only the fault detection and diagnosis can be realized simultaneously but also the accuracy of detection and diagnosis can be guaranteed. Furthermore, the simulation experiments on Tennessee Eastman (TE) benchmark process clearly illustrated the superiority of our proposed strategy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Boosting polyp screening with improved point-teacher weakly semi-supervised

引用

Computers in Biology and Medicine 2025年 191卷 109998-109998页

作者： Du, Xiuquan Zhang, Xuejun Chen, Jiajia Li, Lei Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China Department of Neurology Shuyang Affiliated Hospital of Nanjing University of Traditional Chinese Medicine Suqian China School of Computer Science and Technology Anhui University Hefei China

Polyps, like a silent time bomb in the gut, are always lurking and can explode into deadly colorectal cancer at any time. Many methods are attempted to maximize the early detection of colon polyps by screening, however, there are still face some challenges: (i) the scarcity of per-pixel annotation data and clinical features such as the blurred boundary and low contrast of polyps result in poor performance. (ii) existing weakly semi-supervised methods directly using pseudo-labels to supervise student tend to ignore the value brought by intermediate features in the teacher. To adapt the point-prompt teacher model to the challenging scenarios of complex medical images and limited annotation data, we creatively leverage the diverse inductive biases of CNN and Transformer to extract robust and complementary representation of polyp features (boundary and context). At the same time, a novel designed teacher–student intermediate feature distillation method is introduced rather than just using pseudo-labels to guide student learning. Comprehensive experiments demonstrate that our proposed method effectively handles scenarios with limited annotations and exhibits good segmentation performance. All code is available at https://***/dxqllp/WSS-Polyp. © 2025 Elsevier Ltd

关键词： Weakly semi-supervised Medical image segmentation Boundary extraction Feature distillation

来源：评论

学校读者我要写书评

暂无评论

GateM2Former: Gated Feature Selection and Expert Modeling in Multimodal Emotion Recognition

GateM2Former: Gated Feature Selection and Expert Modeling in...

引用

International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Weixiang Xu Zhongren Dong Runming Wang Xinzhou Xu Zixing Zhang College of Computer Science and Electronic Engineering Hunan University China School of Information Science and Engineering Hunan Normal University China Signal Processing and Speech Communication Laboratory Graz University of Technology Austria Shenzhen Research Institute Hunan University China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

In recent years, multimodal emotion recognition (MER) has gained significant attention due to its potential to integrate information from diverse signals. However, existing methods often struggle to effectively capture complex interactions and contextual information both inter- and intra-modalities, and even to extract the salient representations from pre-trained models. To address these issues, we propose a novel model, gated Mixture of Multimodal Experts (MoME) and Mixtral of Experts (MixMoE) models, namely GateM 2 Former. The gate mechanism is used to select the most relevant representations from pre-trained models. The MoME and MixMoE expert modules respectively learn the individual characteristics of each modality and the intrinsic alignment and potential interactions between modalities. Besides, we design a hierarchical merge structure to better suit the long sequence scenario (i. e., speech in our case). To verify the effectiveness of the introduced model, we conducted extensive experiments on the IEMOCAP and MELD datasets. The results show that GateM 2 Former, with a universal multimodal structure, is able to achieve the best results on IEMOCAP and MELD compared with other latest approaches.

关键词： Adaptation models Emotion recognition Semantics Speech recognition Logic gates signal processing Transformers Feature extraction Robustness Speech processing

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：