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Multispectral point cloud superpoint segmentation

science China(Technological sciences) 2024年第4期67卷 1270-1281页

作者： WANG QingWang WANG MingYe ZHANG ZiFeng SONG Jian ZENG Kai SHEN Tao GU YanFeng Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China Yunnan Key Laboratory of Computer Technologies Application Kunming 650500China School of Electronics and Information Engineering Harbin Institute of TechnologyHarbin 150001China

The multitude of airborne point clouds limits the point cloud processing *** are grouped based on similar points,which can effectively alleviate the demand for computing resources and improve processing ***,existing superpoint segmentation methods focus only on local geometric structures,resulting in inconsistent spectral features of points within a *** feature inconsistencies degrade the performance of subsequent ***,this study proposes a novel Superpoint Segmentation method that jointly utilizes spatial Geometric and Spectral information for multispectral point cloud superpoint segmentation(GSI-SS).Specifically,a similarity metric that combines spatial geometry and spectral information is proposed to facilitate the consistency of geometric structures and object attributes within segmented *** the formation of the primary superpoints,an intersuperpoint pointexchange mechanism that maximizes feature consistency within the final superpoints is *** are conducted on two real multispectral point cloud datasets,and the proposed method achieved higher recall,precision,F score,and lower global consistency and feature classification *** experimental results demonstrate the superiority of the proposed GSI-SS over several state-of-the-art methods.

关键词： multispectral point cloud superpoint segmentation over-segmentation spatial-spectral joint metric

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Machine Learning-Based Methods for Materials Inverse Design: A Review

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Computers, Materials & Continua 2025年第2期82卷 1463-1492页

作者： Yingli Liu Yuting Cui Haihe Zhou Sheng Lei Haibin Yuan Tao Shen Jiancheng Yin Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650093China Yunnan Key Laboratory of Computer Technologies Application Kunming University of Science and TechnologyKunming650500China Yunnan Tin Company Limited Tin Industry Branch Gejiu661000China Faculty of Materials Science and Engineering Kunming University of Science and TechnologyKunming650093China

Finding materials with specific properties is a hot topic in materials *** materials design relies on empirical and trial-and-error methods,requiring extensive experiments and time,resulting in high *** the development of physics,statistics,computer science,and other fields,machine learning offers opportunities for systematically discovering new *** through machine learning-based inverse design,machine learning algorithms analyze the mapping relationships between materials and their properties to find materials with desired *** paper first outlines the basic concepts of materials inverse design and the challenges faced by machine learning-based approaches to materials inverse ***,three main inverse design methods—exploration-based,model-based,and optimization-based—are analyzed in the context of different application ***,the applications of inverse design methods in alloys,optical materials,and acoustic materials are elaborated on,and the prospects for materials inverse design are *** authors hope to accelerate the discovery of new materials and provide new possibilities for advancing materials science and innovative design methods.

关键词： Materials inverse design machine learning target properties deep learning new materials discovery

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Content and opinion-enhanced neural model for opinion sentence classification of Chinese microblog comments

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International Journal of information and Communication technology 2023年第4期23卷 371-387页

作者： Xiang, Yan Guo, Junjun Huang, Yuxin Yu, Zhengtao Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China

Opinion sentence classification of Chinese microblog comments aims to recognise those comments with opinions about the specific microblog content, which is the basis of internet public opinion analysis and opinion mining. However, existing opinion sentence classification methods do not consider whether the opinion sentences point at concerned objects or not. To address these issues, we propose a novel neural model, which combines the microblog content relevance-enhanced module and the opinion representation-enhanced module. In the first module, we propose a mutual attention operation that enables the model to extract better features representing microblog content. In the second module, we employ sentiment word embedding and self-attention operations to enhance the ability of the model to extract the opinion features. We evaluate our model using a Chinese microblog comment dataset. Experimental results show that the accuracy of the proposed model is 2%–5% higher than that of the baseline models, which shows that the proposed content relevance-enhancement and attention mechanism are beneficial to this task. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Sentiment analysis

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Efficient OpenMP Based Z-curve Encoding and Decoding Algorithms

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Computers, Materials & Continua 2025年第1期82卷 1313-1327页

作者： Zicheng Zhou Shaowen Sun Teng Liang Mengjuan Li Fengling Xia School of Electronic Science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China School of Communications Information Engineering Yunnan Communications Vocational and Technical CollegeKunming650500China Library Yunnan Normal UniversityKunming650500China Faculty of Civil Aviation and Aeronautics Kunming University of Science and TechnologyKunming650500China

Z-curve’s encoding and decoding algorithms are primely important in many Z-curve-based *** bit interleaving algorithm is the current state-of-the-art algorithm for encoding and decoding *** simple,its efficiency is hindered by the step-by-step coordinate shifting and bitwise *** tackle this problem,we first propose the efficient encoding algorithm LTFe and the corresponding decoding algorithm LTFd,which adopt two optimization methods to boost the algorithm’s efficiency:1)we design efficient lookup tables(LT)that convert encoding and decoding operations into table-lookup operations;2)we design a bit detection mechanism that skips partial order of a coordinate or a Z-value with consecutive 0s in the front,avoiding unnecessary iterative *** propose order-parallel and point-parallel OpenMP-based algorithms to exploit the modern multi-core *** results on discrete,skewed,and real datasets indicate that our point-parallel algorithms can be up to 12.6×faster than the existing algorithms.

关键词： Z-curve lookup table OpenMP bit detection mechanism

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Few-Shot Knowledge Graph Completion with Structure-Aware Graph Attention Network

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Journal of Shanghai Jiaotong university (science) 2024年 1-10页

作者： Yang, Rongtai Shao, Yubin Du, Qingzhi Zhang, Feng Qi, Yuting School of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China

Few-shot knowledge graph completion refers to inferring missing entity using limited instances. A key challenge lies in entity representation, which is complicated by diverse neighbor attributes. Although the entity’s neighborhood topology holds potential to address this, its significance is overlooked in current research. In this paper, we propose a structure-aware graph attention network for few-shot knowledge graph completion. Firstly, to enhance entity representations, we design a structure-aware graph attention encoder to capture the graph’s structural features of nodes, generating embedding for entity pairs. Secondly, a semantic prototype matching network is employed to compute the prediction score. Experiments on the NELL-One and Wiki-One datasets show that our proposed model outperforms the best baseline models by 0.021, 0.026, 0.039, 0.032 and 0.016, 0.064, 0.043, 0.040 in terms of MRR, Hits@10, Hits@5, and Hits@1 metrics, respectively. This demonstrates that our model can effectively leverage neighborhood topological information to improve the accuracy of knowledge completion, and achieve a better generalization. (Figure presented.) © Shanghai Jiao Tong university 2024.

关键词： Knowledge graph

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Broadband tunable instantaneous frequency measurement system based on stimulated Brillouin scattering

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Optoelectronics Letters 2023年第3期19卷 174-178页

作者： LIAO Weijie ZHANG Jiahong CAI Qibin Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China

A broadband tunable instantaneous frequency measurement(IFM)system is designed based on the stimulated Brillouin scattering effect of the highly nonlinear fiber in which the carrier suppressed single sideband modulated signal of the Brillouin frequency shift acts as pump *** amplitude comparison function(ACF)is constructed by the power radio of the two paths in the *** frequency measurement range and measurement accuracy can be tuned by changing the frequency difference of the two phase modulation *** tunable frequency measurement ranges of 2—5 GHz,2—10 GHz,2—15 GHz,2—20 GHz,and 2—24 GHz are realized,and the corresponding measurement accuracies are 3.64 d B/GHz,2.17 d B/GHz,1.87 d B/GHz,1.22 d B/GHz,and 0.77 d B/GHz,respectively.

关键词： tunable scattering pump

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Boundary-Enhanced U2-Net for Simultaneous Four-Chamber Segmentation in Transthoracic Echocardiography

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IEEE Journal of Biomedical and Health Informatics 2025年第6期29卷 4227-4240页

作者： Meng, Yuanqin Chai, Shengjie Xiao, Haoyu Meng, Zhaohui Wang, Qingwang Shen, Tao Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650500 China First Affiliated Hospital of Kunming Medical University Department of Cardiology Kunming650032 China

The heart, responsible for circulating blood throughout our body, contains four chambers. Existing analysis methods primarily focus on one single ventricle. Transthoracic echocardiography provides real-time estimations of cardiac function and enables comprehensive observations of the entire heart, especially through the apical 4-chamber view. However, no current clinical indices evaluate cardiac function considering all four chambers simultaneously. Manual estimation of the four chambers is laborious, inefficient, and complicated by anatomical complexity and variable image quality, including motion artifacts and unclear borders. There is a significant need for a high-performance segmentation tool that can assess all four chambers concurrently. To address this, we collected a clinically representative dataset of 2D apical 4-chamber view echocardiograms, with annotated 4-chamber regions serving as the basis for automatic 4-chamber synergy analysis. We then proposed a boundary-enhanced network, denoted as BeU2-Net, tailored for transthoracic echocardiography 4-chamber segmentation using our private dataset. Specifically, our network employs a two-level nested encoder-decoder architecture, utilizing a segmentation-specific residual U-block with a mixture of receptive fields at each stage to capture multi-level and multi-scale features. A dedicated boundary prediction branch, incorporating edge details, is integrated to enhance boundary segmentation performance. Experiments on both private and public datasets demonstrate that our BeU2-Net possesses superior boundary detection capabilities and achieves high segmentation performance for echocardiographic images. The source code and dataset will be released at https://***/mm666-y/BeU2-Net. © 2013 IEEE.

关键词： Heart

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A U-Shaped Network-Based Grid Tagging Model for Chinese Named Entity Recognition

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Computers, Materials & Continua 2024年第6期79卷 4149-4167页

作者： Yan Xiang Xuedong Zhao Junjun Guo Zhiliang Shi Enbang Chen Xiaobo Zhang Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650504China Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and TechnologyKunming650500China Kunming Enersun Technology Co. Ltd.Kunming650217China

Chinese named entity recognition(CNER)has received widespread attention as an important task of Chinese information *** previous research has focused on individually studying flat CNER,overlapped CNER,or discontinuous ***,a unified CNER is often needed in real-world *** studies have shown that grid tagging-based methods based on character-pair relationship classification hold great potential for achieving unified ***,how to enrich Chinese character-pair grid representations and capture deeper dependencies between character pairs to improve entity recognition performance remains an unresolved *** this study,we enhance the character-pair grid representation by incorporating both local and global ***,we introduce a new approach by considering the character-pair grid representation matrix as a specialized image,converting the classification of character-pair relationships into a pixel-level semantic segmentation *** devise a U-shaped network to extract multi-scale and deeper semantic information from the grid image,allowing for a more comprehensive understanding of associative features between character *** approach leads to improved accuracy in predicting their relationships,ultimately enhancing entity recognition *** conducted experiments on two public CNER datasets in the biomedical domain,namely CMeEE-V2 and *** results demonstrate the effectiveness of our approach,which achieves F1-score improvements of 7.29 percentage points and 1.64 percentage points compared to the current state-of-the-art(SOTA)models,respectively.

关键词： Chinese named entity recognition character-pair relation classification grid tagging U-shaped segmentation network

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MCFF-Net: Multi-Scale Contextual Feature Fusion Network for Polyp Segmentation

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Journal of Shanghai Jiaotong university (science) 2025年 1-13页

作者： Ma, Lei Yan, Jiangkai Shao, Dangguo Li, Jingtao Wang, Jiawei Yan, Yukun Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Yunnan Provincial Key Laboratory of Artificial Intelligence Kunming650500 China

In clinical practice, technologies for automatically segmenting polyps might greatly improve the speed and accuracy of medical diagnosis, significantly reducing the chances of patients developing colorectal cancer. Nevertheless, the segmentation of polyps presents a considerable challenge due to their low contrast, presence of occlusion, and intricate background disturbances. In this paper, we propose an innovative approach for segmenting polyps, called multi-scale contextual feature fusion network for polyp segmentation (MCFF-Net). Specifically, MCFF-Net includes three modules: feature enhancement module (FEM), global-local feature fusion module (GLFF), and cross-scale feature fusion module (CFFM). Among them, FEM is used to improve the features at each scale. Building on this, the CFFM enables comprehensive interaction among the information across various scales, enhancing the diversity of the feature scales extracted. Moreover, the GLFF fuses global-local features to generate a rough object localization map. This map further modulates the fusion features from the CFFM, facilitating more precise segmentation. On five publicly available datasets, our approach not only segments various polyp types but also surpasses existing methods in terms of accuracy and generalizability. © Shanghai Jiao Tong university 2024.

关键词： Diseases

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Tuning the growth of intermetallic compounds at Sn-0.7Cu solder/Cu substrate interface by adding small amounts of indium

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Journal of Materials science & technology 2024年第15期182卷 246-259页

作者： Ancang Yang Yaoping Lu Yonghua Duan Mengnie Li Shanju Zheng Mingjun Peng Faculty of Material Science and Engineering Kunming University of Science and TechnologyKunming 650093China College of Physics and Information Engineering Fuzhou UniversityFuzhou 350108China

The void defect in intermetallic compounds(IMCs)layer at the joints caused by inhomogeneous atomic diffusion is one of the most important factors limiting the further development of Sn-based *** this work,the thermodynamic stability of IMCs(high-temperatureη-Cu_(6)Sn_(5)and o-Cu_(3)Sn phases)was improved by adding small amounts of indium(In),and the IMCs layers with moderate thickness,low defect concentrations and stable interface bonding were successfully *** formation order of compounds and the interfacial orientation relationships in IMCs layers,the atomic diffusion mechanism,and the growth tuning mechanism of In onη-Cu_(6)Sn_(5)and Cu_(3)Sn,after In adding,were discussed com-prehensively by combining calculations and *** is the first time that the classic heteroge-neous nucleation theory and CALPHAD data were used to obtain the critical nucleus radius ofη-Cu_(6)Sn_(5)and Cu_(3)Sn,and to explain in detail the main factors affecting the formation order and location of IMCs at joints during the welding process.A novel and systematic growth model about IMCs layers in the case of doping with alloying elements was *** growth tuning mechanism of In doping onη-Cu_(6)Sn_(5)and Cu_(3)Sn was further clarified based on the proposed model using first-principles *** growth model used in this study can provide insights into the development and design of multiele-ment Sn-based solders.

关键词： Sn-0.7Cu solder IMCs Aging Atomic migration barrier Growth tuning

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