检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Imran, Muhammad Krebs, Jonathan R. Sivaraman, Vishal Balaji Zhang, Teng Kumar, Amarjeet Ueland, Walker R. Fassler, Michael J. Huang, Jinlong Sun, Xiao Wang, Lisheng Shi, Pengcheng Rokuss, Maximilian Baumgartner, Michael Kirchhof, Yannick Maier-Hein, Klaus H. Isensee, Fabian Liu, Shuolin Han, Bing Nguyen, Bong Thanh Shin, Dong-Jin Ji-Woo, Park Choi, Mathew Uhm, Kwang-Hyun Ko, Sung-Jea Lee, Chanwoong Chun, Jaehee Kim, Jin Sung Zhang, Minghui Zhang, Hanxiao You, Xin Gu, Yun Pan, Zhaohong Liu, Xuan Liang, Xiaokun Tiefenthaler, Markus Almar-Munoz, Enrique Schwab, Matthias Kotyushev, Mikhail Epifanov, Rostislav Wodzinski, Marek Müller, Henning Qayyum, Abdul Mazher, Moona Niederer, Steven A. Wang, Zhiwei Yang, Kaixiang Ren, Jintao Korreman, Stine Sofia Gao, Yuchong Zeng, Hongye Zheng, Haoyu Zheng, Rui Yue, Jinghua Zhou, Fugen Liu, Bo Cosman, Alexander Liang, Muxuan Zhao, Chang Upchurch, Gilbert R. Ma, Jun Zhou, Yuyin Cooper, Michol A. Shao, Wei Department of Medicine University of Florida GainesvilleFL32611 United States Department of Surgery University of Florida GainesvilleFL32611 United States Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611 United States Department of Computer Information Science and Engineering University of Florida GainesvilleFL32611 United States Shanghai Jiao Tong University Shanghai China Electronic & Information Engineering School Harbin Institute of Technology [Shenzhen Shenzhen China Division of Medical Image Computing German Cancer Research Center [DKFZ Heidelberg Germany CO. LTD Beijing China MedAI Seoul Korea Republic of Korea University Seoul Korea Republic of Department of Radiation Oncology Yonsei Cancer Center Heavy Ion Therapy Research Institute Yonsei University College of Medicine Seoul Korea Republic of Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Medical University of Innsbruck Innsbruck Austria Novosibirsk State University Novosibirsk Russia AGH University of Krakow Krakow Poland Sierre Switzerland University of Geneva Geneva Switzerland The Sense Innovation and Research Center Sion Switzerland National Heart and Lung Institute Faculty of Medicine Imperial College London London United Kingdom Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Hubei Wuhan China Aarhus University Department of Clinical Medicine Nordre Palle Juul-Jensens Blvd. 11 Aarhus8200 Denmark Shanghaitech University Pudong Shanghai China Image Processing Center Beihang University Beijing China Department of Computer Science and Engineering University of California Santa CruzCA95064 United States Department of Biostatistics University of Florida GainesvilleFL32611 United States University Health Network ON Canada Agronomy Department University of F

Multi-class segmentation of the aorta in computed tomography angiography (CTA) scans is essential for diagnosing and planning complex endovascular treatments for patients with aortic dissections. However, existing methods reduce aortic segmentation to a binary problem, limiting their ability to measure diameters across different branches and zones. Furthermore, no open-source dataset is currently available to support the development of multi-class aortic segmentation methods. To address this gap, we organized the AortaSeg24 MICCAI Challenge, introducing the first dataset of 100 CTA volumes annotated for 23 clinically relevant aortic branches and zones. This dataset was designed to facilitate both model development and validation. The challenge attracted 121 teams worldwide, with participants leveraging state-of-the-art frameworks such as nnU-Net and exploring novel techniques, including cascaded models, data augmentation strategies, and custom loss functions. We evaluated the submitted algorithms using the Dice Similarity Coefficient (DSC) and Normalized Surface Distance (NSD), highlighting the approaches adopted by the top five performing teams. This paper presents the challenge design, dataset details, evaluation metrics, and an in-depth analysis of the top-performing algorithms. The annotated dataset, evaluation code, and implementations of the leading methods are publicly available to support further research. All resources can be accessed at https://***. © 2025, CC BY-NC-SA.

关键词： computerized tomography

来源：评论

学校读者我要写书评

暂无评论

One-dimensional quasi bound states in the continuum with large operation bandwidth in the ω~k space for nonlinear optical applications

arXiv

引用

arXiv 2022年

作者： Sun, Kaili Jiang, Hui Bykov, Dmitry A. Van, Vien Levy, Uriel Cai, Yangjian Han, Zhanghua Shandong Provincial Key Laboratory of Optics and Photonic Devices Center of Light Manipulation and Applications School of Physics and Electronics Shandong Normal University Jinan250358 China Image Processing Systems Institute Branch of the Federal Scientific Research Centre "Crystallography and Photonics" Russian Academy of Sciences 151 Molodogvardeyskaya st. Samara443001 Russia Department of Electrical and Computer Engineering University of Alberta EdmontonT6G 2V4 Canada Department of Applied Physics The center for Nanoscience and Nanotechnology The Hebrew University of Jerusalem Jerusalem Israel

The phenomenon of bound state in the continuum (BIC) with infinite quality factor and lifetime has emerged in recent years in photonics as a new tool of manipulating light-matter interactions. However, most of the investigated structures only support BIC resonances at very few discrete points in the ω~k space. Even when the BIC is switched to a quasi-BIC(QBIC) resonance through perturbation, its frequency will still be located within a narrow spectral band close to that of the original BIC, restricting their applications in many fields where random or multiple input frequencies beyond the narrow band are required. In this work, we demonstrate that a new set of QBIC resonances can be supported by making use of a special binary grating consisting of two alternatingly aligned ridge arrays with the same period and zero-approaching ridge width difference on a slab waveguide. These QBIC resonances are distributed continuously over a broad band along a line in the ω~k space and can thus be considered as one-dimensional QBICs. With the Q factors generally affected by the ridge difference, it is now possible to choose arbitrarily any frequencies on the dispersion line to achieve significantly enhanced light-matter interactions, facilitating many applications where multiple input wavelengths are required, e.g. sum or difference frequency generations in nonlinear optics. Copyright © 2022, The Authors. All rights reserved.

关键词： Resonance

来源：评论

学校读者我要写书评

暂无评论

Opinion Dynamics Incorporating Higher-Order Interactions

Opinion Dynamics Incorporating Higher-Order Interactions

引用

IEEE International Conference on Data Mining (ICDM)

作者： Zuobai Zhang Wanyue Xu Zhongzhi Zhang Guanrong Chen School of Computer Science Fudan University Shanghai China Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai China Department of Electrical Engineering City University of Hong Kong Hong Kong SAR China

ISBN: (数字)9781728183169

ISBN: (纸本)9781728183176

The issue of opinion sharing and formation has received considerable attention in the academic literature, and a few models have been proposed to study this problem. However, existing models are limited to the interactions among nearest neighbors, ignoring those second, third, and higher-order neighbors, despite the fact that higher-order interactions occur frequently in real social networks. In this paper, we develop a new model for opinion dynamics by incorporating long-range interactions based on higher-order random walks. We prove that the model converges to a fixed opinion vector, which may differ greatly from those models without higher-order interactions. Since direct computation of the equilibrium opinions is computationally expensive, which involves the operations of huge-scale matrix multiplication and inversion, we design a theoretically convergence-guaranteed estimation algorithm that approximates the equilibrium opinion vector nearly linearly in both space and time with respect to the number of edges in the graph. We conduct extensive experiments on various social networks, demonstrating that the new algorithm is both highly efficient and effective.

关键词： Social networking (online) Computational modeling Heuristic algorithms Estimation Approximation algorithms Graph theory Sparse matrices

来源：评论

学校读者我要写书评

暂无评论

Photo-assisted technologies for environmental remediation

Nature Reviews Clean Technology

引用

Nature Reviews Clean Technology 2025年第3期1卷 1-15页

作者： Bo Weng Jiangquan Lv Ning Han Bao-Lian Su Maarten Roeffaers Johan Hofkens Yongfa Zhu Shaobin Wang Wonyong Choi State Key Laboratory of Advanced Environmental Technology Institute of Urban Environment Chinese Academy of Sciences Xiamen China University of Chinese Academy of Sciences Beijing China College of Electronics and Information Science Fujian Jiangxia University Fuzhou China Department of Electrical and Computer Engineering University of Toronto Toronto Canada Laboratory of Living Materials at the State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology Wuhan China cMACS Department of Microbial and Molecular Systems KU Leuven Leuven Belgium Department of Chemistry KU Leuven Leuven Belgium Department of Chemistry Tsinghua University Beijing China School of Chemical Engineering University of Adelaide Adelaide South Australia Australia Department of Energy Engineering Korea Institute of Energy Technology (KENTECH) Naju South Korea

Industrial processes can lead to air and water pollution, particularly from organic contaminants such as toluene and antibiotics, posing threats to human health. Photo-assisted chemical oxidation technologies leverage light energy to mineralize these contaminants. In this Review, we discuss the mechanisms and efficiencies of photo-assisted advanced oxidation processes for wastewater treatment and photothermal technologies for air purification. The integration of solar energy enhances degradation efficiency and reduces energy consumption, enabling more efficient remediation methods. We evaluate the technological aspects of photo-assisted technologies, such as photo-Fenton, photo-persulfate activation, photo-ozonation and photoelectrochemical oxidation, emphasizing their potential for practical applications. Finally, we discuss the challenges in scaling up photo-assisted technologies for specific environmental remediation needs. Photo-assisted technologies have demonstrated effectiveness in environmental remediation, although large-scale applications remain constrained by high costs. Future potential applications of photo-assisted technologies will require that technology selection be tailored to specific pollution scenarios and engineering processes optimized to minimize costs.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Multistage model for robust face alignment using deep neural networks

arXiv

引用

arXiv 2020年

作者： Wang, Huabin Cheng, Rui Zhou, Jian Tao, Liang Kwan, Hon Keung MOE Key Laboratory of Intelligent Computing and Signal Processing School of Computer Science and Technology Anhui University Hefei Anhui230601 China Department of Electrical and Computer Engineering University of Windsor WindsorONN9B 3P4 Canada

An ability to generalize unconstrained conditions such as severe occlusions and large pose variations remains a challenging goal to achieve in face alignment. In this paper, a multistage model based on deep neural networks is proposed which takes advantage of spatial transformer networks, hourglass networks and exemplar-based shape constraints. First, a spatial transformer - generative adversarial network which consists of convolutional layers and residual units is utilized to solve the initialization issues caused by face detectors, such as rotation and scale variations, to obtain improved face bounding boxes for face alignment. Then, stacked hourglass network is employed to obtain preliminary locations of landmarks as well as their corresponding scores. In addition, an exemplar-based shape dictionary is designed to determine landmarks with low scores based on those with high scores. By incorporating face shape constraints, misaligned landmarks caused by occlusions or cluttered backgrounds can be considerably improved. Extensive experiments based on challenging benchmark datasets are performed to demonstrate the superior performance of the proposed method over other state-of-the-art methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Improving unsupervised domain adaptation by reducing bi-level feature redundancy

arXiv

引用

arXiv 2020年

作者： Wang, Mengzhu Zhang, Xiang Lan, Long Wang, Wei Tan, Huibin Luo, Zhigang Science and Technology on Parallel and Distributed Laboratory College of Computer National University of Defense Technology Changsha China Institute for Quantum State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China DUT-RU International School of Information Science & Engineering Dalian University of Technology DalianLiaoning116000 China Department of Science and Technology on Parallel and Distributed Processing National University of Defense Technology Changsha China

Reducing feature redundancy has shown beneficial effects for improving the accuracy of deep learning models, thus it is also indispensable for the models of unsupervised domain adaptation (UDA). Nevertheless, most recent efforts in the field of UDA ignore this point. Moreover, main schemes realizing this in general independent of UDA purely involve a single domain, thus might not be effective for cross-domain tasks. In this paper, we emphasize the significance of reducing feature redundancy for improving UDA in a bi-level way. For the first level, we try to ensure compact domain-specific features with a transferable decorrelated normalization module, which preserves specific domain information whilst easing the side effect of feature redundancy on the sequel domain-invariance. In the second level, domain-invariant feature redundancy caused by domain-shared representation is further mitigated via an alternative brand orthogonality for better generalization. These two novel aspects can be easily plugged into any BN-based backbone neural networks. Specifically, simply applying them to ResNet50 has achieved competitive performance to the state-of-the-arts on five popular benchmarks. Our code will be available at https://***/dreamkily/gUDA. © 2020, CC BY.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Generative Adversarial Networks with Joint Distribution Moment Matching

引用

Journal of the Operations Research Society of China 2019年第4期7卷 579-597页

作者： Yi-Ying Zhang Chao-Min Shen Hao Feng Preston Thomas Fletcher Gui-Xu Zhang Department of Computer Science East China Normal UniversityShanghai 200062China Shanghai Key Laboratory of Multidimensional Information Processing East China Normal UniversityShanghai 200062China Westlake Institute for Brain-Like Science and Technology Hangzhou 310027China Didi Chuxing Science and Technology Co.Ltd. Beijing 100193China Department of Electrical and Computer Engineering University of VirginiaCharlottesvilleVA 22904USA

Generative adversarial networks(GANs)have shown impressive power in the field of machine *** GANs have focused on unsupervised learning *** recent years,conditional GANs that can generate data with labels have been proposed in semi-supervised learning and have achieved better image quality than traditional *** GANs,however,generally only minimize the difference between marginal distributions of real and generated data,neglecting the difference with respect to each class of the *** address this challenge,we propose the GAN with joint distribution moment matching(JDMM-GAN)for matching the joint distribution based on maximum mean discrepancy,which minimizes the differences of both the marginal and conditional *** learning procedure is iteratively conducted by the stochastic gradient descent and *** evaluate JDMM-GAN on several benchmark datasets,including MNIST,CIFAR-10 and the Extended Yale *** with the state-of-the-art GANs,JDMM-GAN generates more realistic images and achieves the best inception score for CIFAR-10 dataset.

关键词： Generative Adversarial Networks Joint Distribution Moment Matching Maximum mean discrepancy

来源：评论

学校读者我要写书评

暂无评论

Analysis of Negative Capacitance MOSFETs Characteristic with Spacer

Analysis of Negative Capacitance MOSFETs Characteristic with...

引用

International Symposium on VLSI Technology, Systems and Applications

作者： Yu-Chun Lee Sekhar Reddy Kola Chieh-Yang Chen Min-Hui Chuang Yiming Li Parallel and Scientific Computing Laboratory Institute of Biomedical Engineering EECS International Graduate Program Institute of Communications Engineering Department of Electrical and Computer Engineering National Chiao Tung University Hsinchu Taiwan Center for mmWave Smart Radar System and Technologies National Chiao Tung University 1001 Ta-Hsueh Rd Hsinchu Taiwan

ISBN: (数字)9781728142326

ISBN: (纸本)9781728142333

In this work, our study comprises of design and investigation on negative capacitance (NC), metal-oxide-semiconductor (MOS) field effects transistors (MOSFETs) with spacer and source/drain (S/D) overlap engineering. The scope of the work is to boost the performance and high-energy efficiency of the studied NC-MOSFETs by using the ferro electric material (FE). The NC-MOSFETs with the spacer technology can achieve the admirable I on /I off ratio and subthreshold swing (SS), compared with planar MOSFETs. It makes device scaling possible by eliminating the short channel effect (SCE). We further estimated the effect of FE thickness and spacer, which are another critical parameter of obtaining better electrical characteristics and reducing SS.

关键词： Capacitance Iron Semiconductor device modeling MOSFET Integrated circuit modeling Mathematical model Ferroelectric materials

来源：评论

学校读者我要写书评

暂无评论

Experimental realization of Schumacher's information geometric bell inequality

arXiv

引用

arXiv 2021年

作者： Rezaei, Tahereh Aslmarand, Shahabeddin M. Snyder, Robert Khajavi, Behzad Alsing, Paul M. Fanto, Michael Ahn, Doyeol Miller, Warner A. Department of Physics Florida Atlantic University Boca RatonFL33431 United States L3Harris 10001 Jack Finney Blvd CBN018 GreenvilleTX75402 United States Dept of Biomedical Engineering University of Houston HoustonTX77204 United States Air Force Research Laboratory Information Directorate RomeNY13441 United States Center Quantum Information Processing Department of Electrical and Computer Engineering University of Seoul Seoul130-743 Korea Republic of

Quantum mechanics can produce correlations that are stronger than classically allowed. This stronger-than-classical correlation is the "fuel" for quantum computing. In 1991 Schumacher forwarded a beautiful geometric approach, analogous to the well-known result of Bell, to capture non-classicality of this correlation for a singlet state. He used well-established information distance defined on an ensemble of identically-prepared states. He calculated that for certain detector settings used to measure the entangled state, the resulting geometry violated a triangle inequality - a violation that is not possible classically. This provided a novel information-based geometric Bell inequality in terms of a "covariance distance." Here we experimentally-reproduce his construction and demonstrate a definitive violation for a Bell state of two photons based on the usual spontaneous parametric down-conversion in a paired BBO crystal. The state we produced had a visibility of Vad = 0.970. We discuss generalizations to higher dimensional multipartite quantum states. © 2021, CC BY.

关键词： Geometry

来源：评论

学校读者我要写书评

暂无评论

Interpretation of Brain Morphology in Association to Alzheimer's Disease Dementia Classification Using Graph Convolutional Networks on Triangulated Meshes

arXiv

引用

arXiv 2020年

作者： Azcona, Emanuel Besson, Pierre Wu, Yunan Punjabi, Arjun Martersteck, Adam Dravid, Amil Parrish, Todd B. Bandt, S. Kathleen Katsaggelos, Aggelos K. Image and Video Processing Laboratory Department of Electrical and Computer Engineering Northwestern University IL United States Lab Northwestern Memorial Hospital IL United States Neuroimaging Laboratory Department of Radiology Northwestern University IL United States Augmented Intelligence in Medical Imaging Northwestern University IL United States

We propose a mesh-based technique to aid in the classification of Alzheimer's disease dementia (ADD) using mesh representations of the cortex and subcortical structures. Deep learning methods for classification tasks that utilize structural neuroimaging often require extensive learning parameters to optimize. Frequently, these approaches for automated medical diagnosis also lack visual interpretability for areas in the brain involved in making a diagnosis. This work: (a) analyzes brain shape using surface information of the cortex and subcortical structures, (b) proposes a residual learning framework for state-of-the-art graph convolutional networks which offer a significant reduction in learnable parameters, and (c) offers visual interpretability of the network via class-specific gradient information that localizes important regions of interest in our inputs. With our proposed method leveraging the use of cortical and subcortical surface information, we outperform other machine learning methods with a 96.35% testing accuracy for the ADD vs. healthy control problem. We confirm the validity of our model by observing its performance in a 25-trial Monte Carlo cross-validation. The generated visualization maps in our study show correspondences with current knowledge regarding the structural localization of pathological changes in the brain associated to dementia of the Alzheimer's type. Copyright © 2020, The Authors. All rights reserved.

关键词： Mesh generation

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：