检索结果-内蒙古大学图书馆

Conference on computer Vision and Pattern Recognition (CVPR)

作者： Yan Li Bin Ji Xintian Shi Jianguo Zhang Bin Kang Limin Wang Platform and Content Group (PCG) Tencent State Key Laboratory for Novel Software Technology Nanjing University China Department of Computer Science and Engineering Southern University of Science and Technology China

ISBN: (数字)9781728171685

ISBN: (纸本)9781728171692

Temporal modeling is key for action recognition in videos. It normally considers both short-range motions and long-range aggregations. In this paper, we propose a Temporal Excitation and Aggregation (TEA) block, including a motion excitation (ME) module and a multiple temporal aggregation (MTA) module, specifically designed to capture both short- and long-range temporal evolution. In particular, for short-range motion modeling, the ME module calculates the feature-level temporal differences from spatiotemporal features. It then utilizes the differences to excite the motion-sensitive channels of the features. The long-range temporal aggregations in previous works are typically achieved by stacking a large number of local temporal convolutions. Each convolution processes a local temporal window at a time. In contrast, the MTA module proposes to deform the local convolution to a group of sub-convolutions, forming a hierarchical residual architecture. Without introducing additional parameters, the features will be processed with a series of sub-convolutions, and each frame could complete multiple temporal aggregations with neighborhoods. The final equivalent receptive field of temporal dimension is accordingly enlarged, which is capable of modeling the long-range temporal relationship over distant frames. The two components of the TEA block are complementary in temporal modeling. Finally, our approach achieves impressive results at low FLOPs on several action recognition benchmarks, such as Kinetics, Something-Something, HMDB51, and UCF101, which confirms its effectiveness and efficiency.

关键词： Two dimensional displays Videos Spatiotemporal phenomena Optical imaging Feature extraction Three-dimensional displays Stacking

来源：评论

学校读者我要写书评

暂无评论

Nearest neighborhood-based deep clustering for source data-absent unsupervised domain adaptation

arXiv

引用

arXiv 2021年

作者： Tang, Song Yang, Yan Ma, Zhiyuan Hendrich, Norman Zeng, Fanyu Ge, Shuzhi Sam Zhang, Changshui Zhang, Jianwei The Institute of Machine Intelligence University of Shanghai for Science and Technology Shanghai China The State Key Laboratory of Electronic Thin Films and Integrated Devices University of Electronic Science and Technology of China Chengdu China Group Department of Informatics Universität Hamburg Hamburg Germany The Institute of Machine Intelligence University of Shanghai for Science and Technology Shanghai China The State Key Lab. for Novel Software Technology Nanjing University Nanjing China The Engineering Research Center of Wideband Wireless Communication Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing China The Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore The Department of Automation Tsinghua University Beijing China

In the classic setting of unsupervised domain adaptation (UDA), the labeled source data are available in the training phase. However, in many real-world scenarios, owing to some reasons such as privacy protection and information security, the source data is inaccessible, and only a model trained on the source domain is available. This paper proposes a novel deep clustering method for this challenging task. Aiming at the dynamical clustering at feature-level, we introduce extra constraints hidden in the geometric structure between data to assist the process. Concretely, we propose a geometry-based constraint, named semantic consistency on the nearest neighborhood (SCNNH), and use it to encourage robust clustering. To reach this goal, we construct the nearest neighborhood for every target data and take it as the fundamental clustering unit by building our objective on the geometry. Also, we develop a more SCNNH-compliant structure with an additional semantic credibility constraint, named semantic hyper-nearest neighborhood (SHNNH). After that, we extend our method to this new geometry. Extensive experiments on three challenging UDA datasets indicate that our method achieves state-of-the-art results. The proposed method has significant improvement on all datasets (as we adopt SHNNH, the average accuracy increases by over 3.0% on the large-scaled dataset). Code is available at https://***/tntek/N2DCX. Copyright © 2021, The Authors. All rights reserved.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Relaxing Relationship Queries on Graph Data

arXiv

引用

arXiv 2020年

作者： Li, Shuxin Cheng, Gong Li, Chengkai National Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China Department of Computer Science and Engineering University of Texas at Arlington ArlingtonTX United States

In many domains we have witnessed the need to search a large entity-relation graph for direct and indirect relationships between a set of entities specified in a query. A search result, called a semantic association (SA), is typically a compact (e.g., diameter-constrained) connected subgraph containing all the query entities. For this problem of SA search, efficient algorithms exist but will return empty results if some query entities are distant in the graph. To reduce the occurrence of failing query and provide alternative results, we study the problem of query relaxation in the context of SA search. Simply relaxing the compactness constraint will sacrifice the compactness of an SA, and more importantly, may lead to performance issues and be impracticable. Instead, we focus on removing the smallest number of entities from the original failing query, to form a maximum successful sub-query which minimizes the loss of result quality caused by relaxation. We prove that verifying the success of a sub-query turns into finding an entity (called a certificate) that satisfies a distance-based condition about the query entities. To efficiently find a certificate of the success of a maximum sub-query, we propose a best-first search algorithm that leverages distance-based estimation to effectively prune the search space. We further improve its performance by adding two fine-grained heuristics: one based on degree and the other based on distance. Extensive experiments over popular RDF datasets demonstrate the efficiency of our algorithm, which is more scalable than baselines. Copyright © 2020, The Authors. All rights reserved.

关键词： Resource Description Framework (RDF)

来源：评论

学校读者我要写书评

暂无评论

Sum of squares: a new metric for NFV service chain placement in edge computing environments and efficient heuristic algorithms

引用

CCF Transactions on Networking 2020年第2期3卷 140-153页

作者： Chen, Zhiqi Zhang, Sheng Qian, Zhuzhong Wang, Can Xiao, Mingjun Wu, Jie Lu, Sanglu State Key Lab. for Novel Software Technology Nanjing University Nanjing P.R. China School of Computer Science and Technology/Suzhou Institute for Advanced Study University of Science and Technology of China Hefei China Center for Networked Computing Temple University Philadelphia USA

Both network function virtualization (NFV) and edge computing (EC), especially the latter, are attracting more and more attention in recent years. A growing number of network service providers are migrating their services from the cloud to the edge for better QoS services, while the recent researches on NFV also concentrate on deploying NFV services in edge computing networks. However, NFV deployment in edge networks is a troublesome challenge and is fairly alien from conventional NFV deployment problems in data centres. Edge network differs from the data center network in the following two aspects: firstly, edge nodes are constrained in computing capacity, and secondly, the network connections between edge nodes are unstable and dynamic, which may show large variance over time. This means edge computing should be designed for high-efficient use of physical edge nodes’ resources. To address the challenges above, we investigate a new NFV Service Chain Placement problem in edge computing environments (NSCP-EC) in this paper. We first prove that the NSCP-EC problem is NP-complete. Then we propose a new metric which can better measure the capacity utilization rate of physical resources, and analyze its advantages with details. Based on the new metric, we propose two heuristic but efficient algorithms called MINI and MINI-tree. To confirm the performance of the two algorithms, we conduct simulations. The result demonstrates that MINI gains an advantage over genetic algorithm (GA) and MINI-tree orevails over MINI in tree topology conditions in the aspects of physical resource utilization, acceptance rate and running time. Both theoretical analysis and simulation results confirm the feasibility of the algorithms.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Satellite Federated Fine-Tuning for Foundation Models in Space Computing Power Networks

arXiv

引用

arXiv 2025年

作者： Zhu, Yan Zhu, Jingyang Wang, Ting Shi, Yuanming Jiang, Chunxiao Letaief, Khaled Ben MoE Engineering Research-Center of Software/Hardware Co-design Technology and Application The Shanghai Key Lab. of Trustworthy Computing East China Normal University Shanghai200062 China School of Information Science and Technology ShanghaiTech University Shanghai201210 China Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

Advancements in artificial intelligence (AI) and low-earth orbit (LEO) satellites have promoted the application of large remote sensing foundation models for various downstream tasks. However, direct downloading of these models for fine-tuning on the ground is impeded by privacy concerns and limited bandwidth. Satellite federated learning (FL) offers a solution by enabling model fine-tuning directly on-board satellites and aggregating model updates without data downloading. Nevertheless, for large foundation models, the computational capacity of satellites is insufficient to support effective on-board fine-tuning in traditional satellite FL frameworks. To address these challenges, we propose a satellite-ground collaborative federated fine-tuning framework. The key of the framework lies in how to reasonably decompose and allocate model components to alleviate insufficient on-board computation capabilities. During fine-tuning, satellites exchange intermediate results with ground stations or other satellites for forward propagation and back propagation, which brings communication challenges due to the special communication topology of space transmission networks, such as intermittent satellite-ground communication, short duration of satellite-ground communication windows, and unstable inter-orbit inter-satellite links (ISLs). To reduce transmission delays, we further introduce tailored communication strategies that integrate both communication and computing resources. Specifically, we propose a parallel intra-orbit communication strategy, a topology-aware satellite-ground communication strategy, and a latency-minimalization inter-orbit communication strategy to reduce space communication costs. Simulation results demonstrate significant reductions in training time with improvements of approximately 33%. Copyright © 2025, The Authors. All rights reserved.

关键词： Satellite communication systems

来源：评论

学校读者我要写书评

暂无评论

A novel approach to reducing information leakage for quantum key distribution

arXiv

引用

arXiv 2021年

作者： Mao, Hao-Kun Zhao, Qiang Qiao, Yu-Cheng Yan, Bing-Ze Xu, Bing-Jie Abd El-Latif, Ahmed A. Li, Qiong Department of Computer Science and Technology Harbin Institute of Technology Harbin150080 China College of Software Engineering ZhengZhou University of Light Industry ZhengZhou450053 China Guangxi Key Lab Cryptography & Information Security Guilin University of Electronic Technology Guangxi Guilin541004 China Science and Technology on Security Communication Laboratory Institute of Southwestern Communication Chengdu610041 China Department of Mathematics and Computer Science Faculty of Science Menoufia University Shebin El-Koom Egypt

Quantum key distribution (QKD) is an important branch of quantum information science as it holds promise for unconditionally secure communication. For QKD research, a central issue is to improve the final secure key rate (SKR) and the maximal transmission distance. To address this issue, most works focused on reducing the information leakage of QKD. In this paper, we propose a novel approach to further reduce the information leakage by specially considering the overlap between the information leakage of quantum part and post-processing part. The overlap means that the information leakage of post-processing part caused solely by multi-photon pulses is considered twice in previous studies, i.e., both in quantum part and post-processing part. Since the information carried by multi-photon pulses has been considered as completely known by Eve through the photon-number-splitting attack in quantum part, there is no need to consider it in post-processing part repetitively during the SKR calculation. Therefore, our approach can theoretically reduce the information leakage of a QKD protocol. Based on this idea, we derive the formulas to calculate the amount of information leakage for decoy-BB84 and sending-or-not-sending twin-field protocols. Simulation results for these two typical protocols also demonstrate that our approach evidently improves the SKR as well as the maximal transmission distance under practical experimental parameters. Copyright © 2021, The Authors. All rights reserved.

关键词： Quantum cryptography

来源：评论

学校读者我要写书评

暂无评论

Disjoint-Path and Golden-Pin Based Irregular PCB Routing with Complex Constraints 23

Disjoint-Path and Golden-Pin Based Irregular PCB Routing wit...

引用

Proceedings of the 60th Annual ACM/IEEE Design Automation Conference

作者： Qinghai Liu Qinfei Tang Jiarui Chen Chuandong Chen Ziran Zhu Huan He Jianli Chen Yao-Wen Chang Center for Discrete Mathematics Fuzhou University Fuzhou China and Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou China Center for Discrete Mathematics Fuzhou University Fuzhou China College of Computer and Date Science Fuzhou University Fuzhou China Department of Microelectronics Fuzhou University Fuzhou China Department of Microelectronics Southeast University Nanjing China Hangzhou Huawei Enterprises Telecommunication Technologies Co. Ltd Hangzhou China State Key Lab of ASIC & System Fudan University Shanghai China Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan and Department of Electrical Engineering National Taiwan University Taipei Taiwan

ISBN: (纸本)9798350323481

PCB routing becomes time-consuming as the complexity of PCB design increases. Unlike traditional schemes that treat the two essential PCB routing processes separately, namely, escape and bus routing, we consider the continuity between them and present a golden-pin-based routing scheme to find the desired solution with angle and topology constraints. Further, conventional rip-up and reroute methods are often ineffective and inefficient for congestion alleviation and routability optimization. We construct a component graph by modeling components as vertices and applying the minimum weight vertex covering method to improve the routability. A self-adaptable ordering method is presented for escape routing to arrange the pin order on the component boundary, guaranteeing successful bus routing. In addition, escape routing is performed based on a disjoint path method. We construct a dynamic Hanan grid in bus routing and utilize a novel congestion adjustment technique to improve solution quality. Compared with FreeRouting and Allegro, the experiment results show that our algorithm achieves high routability and a significant 90% runtime reduction.

关键词： escape routing

来源：评论

学校读者我要写书评

暂无评论

Online Reflective Learning for Robust Medical Image Segmentation

arXiv

引用

arXiv 2022年

作者： Huang, Yuhao Yang, Xin Huang, Xiaoqiong Liang, Jiamin Zhou, Xinrui Chen, Cheng Dou, Haoran Hu, Xindi Cao, Yan Ni, Dong National-Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Biomedical Engineering Health Science Center Shenzhen University China Lab Shenzhen University China Marshall Laboratory of Biomedical Engineering Shenzhen University China Department of Computer Science and Engineering The Chinese University of Hong Kong China University of Leeds United Kingdom Shenzhen RayShape Medical Technology Co. Ltd China

Deep segmentation models often face the failure risks when the testing image presents unseen distributions. Improving model robustness against these risks is crucial for the large-scale clinical application of deep models. In this study, inspired by human learning cycle, we propose a novel online reflective learning framework (RefSeg) to improve segmentation robustness. Based on the reflection-on-action conception, our RefSeg firstly drives the deep model to take action to obtain semantic segmentation. Then, RefSeg triggers the model to reflect itself. Because making deep models realize their segmentation failures during testing is challenging, RefSeg synthesizes a realistic proxy image from the semantic mask to help deep models build intuitive and effective reflections. This proxy translates and emphasizes the segmentation flaws. By maximizing the structural similarity between the raw input and the proxy, the reflection-on-action loop is closed with segmentation robustness improved. RefSeg runs in the testing phase and is general for segmentation models. Extensive validation on three medical image segmentation tasks with a public cardiac MR dataset and two in-house large ultrasound datasets show that our RefSeg remarkably improves model robustness and reports state-of-the-art performance over strong competitors. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

An ANTLR-based flattening framework for AltaRica 3.0 model

引用

International Journal of Performability Engineering 2019年第9期15卷 2462-2475页

作者： Hu, Jun Chen, Shuo Chen, Defeng Kang, Jiexiang Wang, Hui College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China Department of Software China National Aeronautic Radio Electronics Research Institute Shanghai200233 China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing210007 China School of Mechanical Engineering Hefei University of Technology Hefei230601 China

AltaRica is a modeling language that is capable of hierarchical modelling and fault behavior description for industrial safety-critical system design. AltaRica 3.0 is the latest version, and its semantics are based on a formal GTS (Guarded Transition Systems) model. One of the key steps in the process of safety analysis toward AltaRica 3.0 models is that how to flatten a hierarchical AltaRica 3.0 model into a semantically equivalent GTS semantic model. This paper proposes an AltaRica 3.0 model flattening algorithm framework based on ANTLR (Another Tool for Language Recognition). Firstly, considering the different structural features of Block and Class, the AltaRica 3.0 model is sliced carefully in order to obtain the corresponding AST (Abstract Syntax Tree). Secondly, a set of recursive transformation algorithms are designed to extract and transform the AltaRica model elements, which are stored in the AST nodes based on the traversal technique of the AST. Then, a semantically equivalent flattened GTS model can be obtained. Lastly, several case studies show that the algorithms designed in this paper can effectively implement the flattening process of AltaRica 3.0 models. © 2019 Totem Publisher, Inc. All rights reserved.

关键词： Modeling languages

来源：评论

学校读者我要写书评

暂无评论

Erratum to: CA-DTS: A Distributed and Collaborative Task Scheduling Algorithm for Edge Computing Enabled Intelligent Road Network

引用

Journal of computer science and technology 2023年第6期38卷 1451-1451页

作者： Hu, Shi-Hong Luo, Qu-Yuan Li, Guang-Hui Shi, Weisong Ye, Bao-Liu Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai University Nanjing China School of Computer and Information Hohai University Nanjing China School of Information Science and Technology Southwest Jiaotong University Chengdu China School of Artificial Intelligence and Computer Science Jiangnan University Wuxi China Department of Computer and Information Sciences University of Delaware Newark USA National Key Laboratory for Novel Software Technology Nanjing University Nanjing China

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：