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TBGA-Net: Trigonometric Bilinear Attention and Global-aware Aggregation Network for Large-Scale 3D Point Cloud Segmentation

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IEEE Transactions on Circuits and systems for Video technology 2025年

作者： Wang, Jianing Hao, Shengjia Hua, Zheng Yao, Yuqiong Xu, Qiong Liu, Bo Gong, Maoguo Xidian University Key Laboratory of Collaborative Intelligence Systems Ministry of Education School of Computer Science and Technology Xi'an710071 China Xidian University Key Laboratory of Intelligent Perception and Image Understanding Ministry of Education of China School of Artificial Intelligence Xi'an710071 China Chinese Academy of Science Institute of High Energy Physics China Xidian University Key Laboratory of Collaborative Intelligence Systems Ministry of Education Xi'an710071 China

The unstructured, unordered and inherent irregular sampling properties presents difficulties for accurate and efficient realizing semantic segmentation of large-scale 3D point cloud. The complexity and the long-distance information exploitation are the key challenges for large-scale 3D point cloud semantic segmentation. Therefore, in order to efficiently exploit long-distance global information and improve the segmentation accuracy of point cloud data located at the edges of distinct categories, a novel Trigonometric Bilinear attention and Global-aware Aggregation network (TBGA-Net) is designed to integrate and supplement the local-global contextual features for large-scale point clouds segmentation. The proposed Global-aware Context Aggregation block (GCA) can implicitly excavate the global context for each 3D point by utilizing its surface-to-volume ratio of the neighborhood to the global point cloud. Furthermore, aim at refining local-global features, the Trigonometric Bilinear Attention block (TBA) utilizes trigonometric functions to embed the point cloud coordinates of local regions, and applies bilinear attention to realize feature enhancement for obtaining more discriminative local-global features. Additionally, we further designed a novel Dynamic-adjusting Cross-entropy Loss (DCLoss) to incorporate with TBGA-Net for addressing the issue of class imbalance in training data for large-scale 3D point cloud semantic segmentation. The experimental results on three 3D point cloud datasets demonstrates that the proposed algorithm indicates better segmentation accuracy especially for the point located at the boundary of the distinct categories. © 1991-2012 IEEE.

关键词： Semantic Segmentation

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Progressive Dual Priori Network for Generalized Breast Tumor Segmentation

arXiv

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arXiv 2023年

作者： Wang, Li Wang, Lihui Kuai, Zixiang Tang, Lei Ou, Yingfeng Ye, Chen Zhu, Yuemin Wu, Min Shi, Tianliang Engineering Research Center of Text Computing & Cognitive Intelligence Ministry of Education Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guiyang550025 China Imaging Center Harbin Medical University Cancer Hospital Harbin150081 China Radiology Department Guizhou Provincial People’s Hospital Guiyang550002 China Radiology Department Tongren People’s Hospital Tongren554300 China Univ Lyon INSA Lyon CNRS Inserm CREATIS UMR 5220 U1206 LyonF-69621 France

To promote the generalization ability of breast tumor segmentation models, as well as to improve the segmentation performance for breast tumors with smaller size, low-contrast and irregular shape, we propose a progressive dual priori network (PDPNet) to segment breast tumors from dynamic enhanced magnetic resonance images (DCE-MRI) acquired at different centers. The PDPNet first cropped tumor regions with a coarse-segmentation based localization module, then the breast tumor mask was progressively refined by using the weak semantic priori and cross-scale correlation prior knowledge. To validate the effectiveness of PDPNet, we compared it with several state-of-the-art methods on multi-center datasets. The results showed that, comparing against the suboptimal method, the DSC and HD95 of PDPNet were improved at least by 5.13% and 7.58% respectively on multi-center test sets. In addition, through ablations, we demonstrated that the proposed localization module can decrease the influence of normal tissues and therefore improve the generalization ability of the model. The weak semantic priors allow focusing on tumor regions to avoid missing small tumors and low-contrast tumors. The cross-scale correlation priors are beneficial for promoting the shape-aware ability for irregular tumors. Thus integrating them in a unified framework improved the multicenter breast tumor segmentation performance. The source code and open data can be accessed at https://github. com/wangli100209/PDPNet. Copyright © 2023, The Authors. All rights reserved.

关键词： Magnetic resonance

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A review of evolutionary multi-modal multi-objective optimization

arXiv

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arXiv 2020年

作者： Tanabe, Ryoji Ishibuchi, Hisao Shenzhen Key Laboratory of Computational Intelligence University Key Laboratory of Evolving Intelligent Systems of Guangdong Province Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

Multi-modal multi-objective optimization aims to find all Pareto optimal solutions including overlapping solutions in the objective space. Multi-modal multi-objective optimization has been investigated in the evolutionary computation community since 2005. However, it is difficult to survey existing studies in this field because they have been independently conducted and do not explicitly use the term "multi-modal multi-objective optimization". To address this issue, this paper reviews existing studies of evolutionary multi-modal multi-objective optimization, including studies published under names that are different from "multi-modal multi-objective optimization". Our review also clarifies open issues in this research area. Copyright © 2020, The Authors. All rights reserved.

关键词： Multiobjective optimization

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A niching indicator-based multi-modal many-objective optimizer

arXiv

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arXiv 2020年

Multi-modal multi-objective optimization is to locate (almost) equivalent Pareto optimal solutions as many as possible. Some evolutionary algorithms for multi-modal multi-objective optimization have been proposed in the literature. However, there is no efficient method for multi-modal many-objective optimization, where the number of objectives is more than three. To address this issue, this paper proposes a niching indicator-based multi-modal multi- and many-objective optimization algorithm. In the proposed method, the fitness calculation is performed among a child and its closest individuals in the solution space to maintain the diversity. The performance of the proposed method is evaluated on multi-modal multi-objective test problems with up to 15 objectives. Results show that the proposed method can handle a large number of objectives and find a good approximation of multiple equivalent Pareto optimal solutions. The results also show that the proposed method performs significantly better than eight multi-objective evolutionary algorithms. Copyright © 2020, The Authors. All rights reserved.

关键词： Multiobjective optimization

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An easy-to-use real-world multi-objective optimization problem suite

arXiv

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arXiv 2020年

Although synthetic test problems are widely used for the performance assessment of evolutionary multi-objective optimization algorithms, they are likely to include unrealistic properties which may lead to overestimation/underestimation. To address this issue, we present a multi-objective optimization problem suite consisting of 16 bound-constrained real-world problems. The problem suite includes various problems in terms of the number of objectives, the shape of the Pareto front, and the type of design variables. 4 out of the 16 problems are multi-objective mixed-integer optimization problems. We provide Java, C, and Matlab source codes of the 16 problems so that they are available in an off-the-shelf manner. We examine an approximated Pareto front of each test problem. We also analyze the performance of six representative evolutionary multi-objective optimization algorithms on the 16 problems. In addition to the 16 problems, we present 8 constrained multi-objective real-world problems. Copyright © 2020, The Authors. All rights reserved.

关键词： Multiobjective optimization

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Physical-barrier detection based collective motion analysis

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Frontiers of computer science 2019年第2期13卷 426-436页

作者： Gaoqi HE Qi CHEN Dongxu JIANG Yubo YUAN Xingjian LU Department of Computer Science and Engineering East China University of Science and Technology Shanghai 200237 China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing 100191 China Smart City Collaborative Innovation Center Shanghai Jiao Tong University Shanghai 200240 China

Collective motion is one of the most fascinating phenomena and mainly caused by the interactions between individuals. Physical-barriers, as the particular facilities which divide the crowd into different lanes, greatly affect the measurement of such interactions. In this paper we propose the physical-barrier detection based collective motion analysis (PDCMA) approach. The main idea is that the interaction between spatially adjacent pedestrians actually does not exist if they are separated by the physical-barrier. Firstly, the physical-barriers are extracted by two-stage clustering. The scene is automatically divided into several motion regions. Secondly, local region collectiveness is calculated to represent the interactions between pedestrians in each region. Finally, extensive evaluations use the three typical methods, i.e., the PDCMA, the Collectiveness, and the average normalized Velocity, to show the efficiency and efficacy of our approach in the scenes with and without physical barriers. Moreover, several escalator scenes are selected as the typical physical-barrier test scenes to demonstrate the performance of our approach. Compared with the current collective motion analysis methods, our approach better adapts to the scenes with physical barriers.

关键词： crowd behavior analysis collective motion physical-barrier detection two-stage clustering local region collectiveness

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Model Test on the Development of Artificial Freezing Curtain in Gravelly Soil Layer Under Seepage

SSRN

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SSRN 2024年

作者： Yuan, Chang Kong, Xiangbing Chen, Xin Lei, Lele Li, Dongwei Lai, Yuanming East China University of Technology Jiangxi Nanchang330013 China Geological Environment and Underground Space Engineering Research Center of Jiangxi Province Jiangxi Nanchang330013 China State Key Laboratory of Frozen Soil Engineering Northwest Institute of Eco-Environment and Resources CAS Gansu Lanzhou730000 China Université du Québec à Rimouski Department of Mathematics Computer Science and Engineering Canada Dalian University Liaoning Dalian116622 China South China University of Technology China

To investigate the development of artificial freezing curtain under seepage, model tests have been conducted in gravelly soil layer. The test results exhibit that the strong seepage of 7.5 m/d affects the formation of frozen curtain much greater than lower seepage below 5 m/d. With the seepage velocity increasing, the temperature field of the freezing curtain distributes asymmetrically gradually, and the curtain tends to close upstream, resulting in a notable increase of frozen time and closure time. Along the freezing pipe circle from the upstream to the downstream, the thickness of curtain is almost in a linearly increasing tendency. A Boltzmann unfrozen water content is used to express the measured unfrozen water content variation with temperature, and a hydro-thermal coupling model has been proposed to describe the developing process of artificial freezing curtain accounting for seepage and ice-water phase change. These findings indicate that the strong influence of strong seepage should be highly paid attention in artificial freezing engineering. © 2024, The Authors. All rights reserved.

关键词： Seepage

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An analysis of quality indicators using approximated optimal distributions in a Three-dimensional objective space

arXiv

引用

arXiv 2020年

Although quality indicators play a crucial role in benchmarking evolutionary multi-objective optimization algorithms, their properties are still unclear. One promising approach for understanding quality indicators is the use of the optimal distribution of objective vectors that optimizes each quality indicator. However, it is difficult to obtain the optimal distribution for each quality indicator, especially when its theoretical property is unknown. Thus, optimal distributions for most quality indicators have not been well investigated. To address these issues, first, we propose a problem formulation of finding the optimal distribution for each quality indicator on an arbitrary Pareto front. Then, we approximate the optimal distributions for nine quality indicators using the proposed problem formulation. We analyze the nine quality indicators using their approximated optimal distributions on eight types of Pareto fronts of three-objective problems. Our analysis demonstrates that uniformly-distributed objective vectors over the entire Pareto front are not optimal in many cases. Each quality indicator has its own optimal distribution for each Pareto front. We also examine the consistency among the nine quality indicators. Copyright © 2020, The Authors. All rights reserved.

关键词： Benchmarking

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Review and analysis of three components of differential evolution mutation operator in MOEA/D-DE

arXiv

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arXiv 2020年

A decomposition-based multi-objec evolutionary algorithm with a differential evolution variation operator (MOEA/D-DE) shows high performance on challenging multi-objective problems (MOPs). The DE mutation consists of three key components: a mutation strategy, an index selection method for parent individuals, and a bound-handling method. However, the configuration of the DE mutation operator that should be used for MOEA/D-DE has not been thoroughly investigated in the literature. This configuration choice confuses researchers and users of MOEA/D-DE. To address this issue, we present a review of the existing configurations of the DE mutation operator in MOEA/DDE and systematically examine the influence of each component on the performance of MOEA/D-DE. Our review reveals that the configuration of the DE mutation operator differs depending on the source code of MOEA/D-DE. In our analysis, a total of 30 configurations (three index selection methods, two mutation strategies, and five bound handling methods) are investigated on 16 MOPs with up to five objectives. Results show that each component significantly affects the performance of MOEA/D-DE. We also present the most suitable configuration of the DE mutation operator, which maximizes the effectiveness of MOEA/D-DE. Copyright © 2020, The Authors. All rights reserved.

关键词： Multiobjective optimization

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Phyllotaxis-inspired nanosieves with multiplexed orbital angular momentum

引用

eLight 2021年第1期1卷 46-56页

作者： Zhongwei Jin David Janoschka Junhong Deng Lin Ge Pascal Dreher Bettina Frank Guangwei Hu Jincheng Ni Yuanjie Yang Jing Li Changyuan Yu Dangyuan Lei Guixin Li Shumin Xiao Shengtao Mei Harald Giessen Frank Meyer zu Heringdorf Cheng-Wei Qiu Department of Electrical and Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117583Singapore College of Optical and Electronic Technology China Jiliang UniversityHangzhou 310018China Faculty of Physics and Center for Nanointegration Duisburg-Essen(CENIDE) University of Duisburg-EssenLotharstrasse 1-2147057 DuisburgGermany Department of Materials Science and Engineering Shenzhen Institute for Quantum Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China Beijing Qianjunyide Technology Co.Ltd Beijing 100031China. Physics Institute and Stuttgart Center of Photonics Engineering(SCoPE) University of Stuttgart70569 Stutt-gartGermany. School of Physics University of ElectronicScience and Technology of ChinaChengdu 611731China. Key Laboratory of Optoelectronic Materials Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190China. Department of Electronic and Information Engineering The Hong Kong Polytechnic UniversityHung HomKowloonHong Kong SARChina. Department of Materials Science and Engineering City University of Hong Kong83 Tat Chee AvenueKowloonHong Kong SARChina. State Key Laboratory On Tunable Laser Technology Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information SystemShenzhen Graduate SchoolHarbin Institute of TechnologyShenzhen 518055China.

Nanophotonic platforms such as metasurfaces,achieving arbitrary phase profiles within ultrathin thickness,emerge as miniaturized,ultracompact and kaleidoscopic optical vortex ***,it is often required to segment or interleave independent sub-array metasurfaces to multiplex optical vortices in a single nano-device,which in turn affects the device’s compactness and channel ***,inspired by phyllotaxis patterns in pine cones and sunflowers,we theoretically prove and experimentally report that multiple optical vortices can be produced in a single compact phyllotaxis nanosieve,both in free space and on a chip,where one meta-atom may contribute to many vortices *** time-resolved dynamics of on-chip interference wavefronts between multiple plasmonic vortices was revealed by ultrafast time-resolved photoemission electron *** nature-inspired optical vortex generator would facilitate various vortex-related optical applications,including structured wavefront shaping,free-space and plasmonic vortices,and high-capacity information metaphotonics.

关键词： Phyllotaxis vortex nanosieve Free-space Plasmonic vortices Ultrafast time-resolved

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