检索结果-内蒙古大学图书馆

IEEE International Conference on Web Services (ICWS)

作者： Qinglan Peng Yunni Xia Yan Wang Chunrong Wu Wanbo Zheng Xin Luo Shanchen Panz Yong Ma Chunxu Jiang Software Theory and Technology Chongqing Key Lab Chongqing University Chongqing China Macquarie University Sydney NSW Australia Data Science Research Center Kunming University of Science and Technology Kunming China Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing China School of Computer and Communication Engineering China University of Petroleum Qingdao China School of Computer and Information Engineering Jiangxi Normal University Nanchang China Chongqing Key Laboratory of Smart Electronics Reliability Technology Chongqing China

ISBN: (数字)9781728187860

ISBN: (纸本)9781728187877

Edge computing is a promising paradigm that can boost the performance of novel mobile applications and energize the real-time governance of Internet-of-Things (IoT) big data. In edge computing, mobile application vendors are allowed to employ edge resources to speed up end-users' applications in an elastic and on-demand manner. However, due to the complex geographical distribution of edge servers and users, how to decide the most appropriate destination edge server to hire and how to decide the corresponding user-server allocation plan with as-low-as-possible monetary cost are the key problems for application vendors. Instead of assuming a simultaneous-batch-arrival pattern of incoming users and considering static optimization of the Edge User Allocation (EUA) problem by most existing studies, in this paper, we consider an online EUA problem where users' arrival and departure follow a general pattern. We take the long-term edge user allocation rate and edge server leasing cost as scheduling targets and propose a decentralized collaborative and fuzzy-control-based approach to yielding real-time user-edge-server allocation schedules. In this approach, edge users are allowed to independently make their own allocation decision only based on local information (i.e., the status of nearby edge servers). Experiments on real-world edge datasets demonstrate our approach outperforms state-of-the-art approaches in terms of long-term allocation rate and system cost.

关键词： Web services Collaboration Real-time systems Mobile applications Resource management Servers Edge computing

来源：评论

学校读者我要写书评

暂无评论

LAVS: A LIGHTWEIGHT AUDIO-VISUAL SALIENCY PREDICTION MODEL

LAVS: A LIGHTWEIGHT AUDIO-VISUAL SALIENCY PREDICTION MODEL

引用

2021 IEEE International Conference on Multimedia and Expo, ICME 2021

作者： Zhu, Dandan Zhao, Defang Min, Xiongkuo Han, Tian Zhou, Qiangqiang Yu, Shaobo Chen, Yongqing Zhai, Guangtao Yang, Xiaokang MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University China School of Software Engineering Tongji University China Institute of Image Communication and Network Engineering Shanghai Jiao Tong University China Department of Computer Science Stevens Institute of Technology United States School of Software Jiangxi Normal University China Information Technology Services East China Normal University China College of Information and Communication Hainan University China

ISBN: (纸本)9781665438643

Audio information is essential for guiding human attention and visual perception, which has been verified by many comprehensive psychological studies. However, the audio modality has been rather neglected in modeling visual attention, most of the current visual attention models heavily depend on visual information. Additionally, current existing high-performing visual attention models rely on deeper convolution neural networks (CNNs), benefiting from their extraordinary feature learning ability but incurring high computational cost. To this end, we propose a novel lightweight audio-visual saliency (LAVS) model to efficiently address the problem of fixation prediction in videos. To the best of our knowledge, our proposed model constitutes the first attempt to exploit a lightweight network and combines the visual and audio cues to perform saliency estimation in videos. Specifically, our proposed model consists of four modules, which are spatial-temporal visual saliency estimation module, audio features extraction module, source sound localization module, and audio-visual saliency fusion module. Extensive experiments across datasets validate the effectiveness and real-time performance of the proposed LAVS model, which outperforms the other state-of-the-art methods. © 2021 IEEE

关键词： Behavioral research

来源：评论

学校读者我要写书评

暂无评论

MESD: Exploring optical flow assessment on edge of motion objects with motion edge structure difference

arXiv

引用

arXiv 2021年

作者： Liao, Bin Hu, Jinlong College of Mathematics and Informatics South China Agricultural University Guangzhou China Guangdong Key Lab of Communication and Computer Network School of Computer Science and Engineering South China University of Technology Guangzhou China

The optical flow estimation has been assessed in various applications. In this paper, we propose a novel method named motion edge structure difference(MESD) to assess estimation errors of optical flow fields on edge of motion objects. We implement comparison experiments for MESD by evaluating five representative optical flow algorithms on four popular benchmarks: MPI Sintel, Middlebury, KITTI 2012 and KITTI 2015. Our experimental results demonstrate that MESD can reasonably and discriminatively assess estimation errors of optical flow fields on motion edge. The results indicate that MESD could be a supplementary metric to existing general assessment metrics for evaluating optical flow algorithms in related computer vision applications. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical flows

来源：评论

学校读者我要写书评

暂无评论

RoKEPG: RoBERTa and Knowledge Enhancement for Prescription Generation of Traditional Chinese Medicine

RoKEPG: RoBERTa and Knowledge Enhancement for Prescription G...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Hua Pu Jiacong Mi Shan Lu Jieyue He School of Computer Science and Engineering Key Lab of Computer Network and Information Integration MOE Southeast University Nanjing China Nanjing Fenghuo Tiandi Communication Technology Co. Ltd Nanjing China

Traditional Chinese medicine (TCM) prescription is the most critical form of TCM treatment, and uncovering the complex nonlinear relationship between symptoms and TCM is of great significance for clinical practice and assisting physicians in diagnosis and treatment. Although there have been some studies on TCM prescription generation, these studies consider a single factor and directly model the symptom-prescription generation problem mainly based on symptom descriptions, lacking guidance from TCM knowledge. To this end, we propose a RoBERTa and Knowledge Enhancement model for Prescription Generation of Traditional Chinese Medicine (RoKEPG). RoKEPG is firstly pre-trained by our constructed TCM corpus, followed by fine-tuning the pre-trained model, and the model is guided to generate TCM prescriptions by introducing four classes of knowledge of TCM through the attention mask matrix. Experimental results on the publicly available TCM prescription dataset show that RoKEPG improves the F 1 metric by about 2% over the baseline model with the best results.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An Open-World, Diverse, Cross-Spatial-Temporal Benchmark for Dynamic Wild Person Re-Identification

arXiv

引用

arXiv 2024年

作者： Zhang, Lei Fu, Xiaowei Huang, Fuxiang Yang, Yi Gao, Xinbo The School of Microelectronics and Communication Engineering Chongqing University Chongqing400044 China Peng Cheng Lab Shenzhen China The College of Computer Science and Technology Zhejiang University Hangzhou310058 China The Chongqing Key Laboratory of Image Cognition Chongqing University of Posts and Telecommunications Chongqing400065 China

Person re-identification (ReID) has made great strides thanks to the data-driven deep learning techniques. However, the existing benchmark datasets lack diversity, and models trained on these data cannot generalize well to dynamic wild scenarios. To meet the goal of improving the explicit generalization of ReID models, we develop a new Open-World, Diverse, Cross-Spatial-Temporal dataset named OWD with several distinct features. 1) Diverse collection scenes: multiple independent open-world and highly dynamic collecting scenes, including streets, intersections, shopping malls, etc. 2) Diverse lighting variations: long time spans from daytime to nighttime with abundant illumination changes. 3) Diverse person status: multiple camera networks in all seasons with normal/adverse weather conditions and diverse pedestrian appearances (e.g., clothes, personal belongings, poses, etc.). 4) Protected privacy: invisible faces for privacy critical applications. To improve the implicit generalization of ReID, we further propose a Latent Domain Expansion (LDE) method to develop the potential of source data, which decouples discriminative identity-relevant and trustworthy domain-relevant features and implicitly enforces domain-randomized identity feature space expansion with richer domain diversity to facilitate domain-invariant representations. Our comprehensive evaluations with most benchmark datasets in the community are crucial for progress, although this work is far from the grand goal toward open-world and dynamic wild applications. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

Meta Invariance Defense Towards Generalizable Robustness to Unknown Adversarial Attacks

arXiv

引用

arXiv 2024年

作者： Zhang, Lei Zhou, Yuhang Yang, Yi Gao, Xinbo School of Microelectronics and Communication Engineering Chongqing University Chongqing400044 China Peng Cheng Lab Shenzhen China College of Computer Science and Technology Zhejiang University Hangzhou310058 China Chongqing Key Laboratory of Image Cognition Chongqing University of Posts and Telecommunications Chongqing400065 China

—Despite providing high-performance solutions for computer vision tasks, the deep neural network (DNN) model has been proved to be extremely vulnerable to adversarial attacks. Current defense mainly focuses on the known attacks, but the adversarial robustness to the unknown attacks is seriously overlooked. Besides, commonly used adaptive learning and fine-tuning technique is unsuitable for adversarial defense since it is essentially a zero-shot problem when deployed. Thus, to tackle this challenge, we propose an attack-agnostic defense method named Meta Invariance Defense (MID). Specifically, various combinations of adversarial attacks are randomly sampled from a manually constructed Attacker Pool to constitute different defense tasks against unknown attacks, in which a student encoder is supervised by multi-consistency distillation to learn the attack-invariant features via a meta principle. The proposed MID has two merits: 1) Full distillation from pixel-, feature- and prediction-level between benign and adversarial samples facilitates the discovery of attack-invariance. 2) The model simultaneously achieves robustness to the imperceptible adversarial perturbations in high-level image classification and attack-suppression in low-level robust image regeneration. Theoretical and empirical studies on numerous benchmarks such as ImageNet verify the generalizable robustness and superiority of MID under various attacks. Copyright © 2024, 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

A tree-based data aggregation scheduling algorithm for wireless sensor networks

引用

Journal of Computational Information Systems 2012年第13期8卷 5409-5416页

作者： Xu, Jian Yang, Geng Liu, Zhipeng Chen, Yunfang College of Computer Science and Technology Nanjing University of Posts and Telecommunications Nanjing 210003 China Key Lab. of Broadband Wireless Communication and Sensor Network Technology of Ministry of Education Nanjing University of Posts and Telecommunications Nanjing 210003 China

Data aggregation is one of the key technologies for Wireless Sensor networks applications. Data aggregation can cut down the data traffic, thereby reduce energy consumption, and extend the network lifetime. But the QoS performance of data aggregation rests with the aggregation scheduling algorithm. The scheduling problems have been extensively studied recently, however most of them must rely on some specific aggregation trees and this restricts the applicability of those algorithms dramatically. In this paper, we proposed an improved scheduling algorithm, which is applicable for arbitrary aggregation tree topology. Based on the characteristics of the structure of the tree, we construct the transfer node set of each time slot, and implement the conflict-free data aggregation scheduling. The results of experiments show that our algorithm can reduce the delay of data aggregation process for various aggregation trees. © 2011 by Binary Information Press.

关键词： Wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

Gridless two-dimensional DOA estimation with L-shaped array based on the cross-covariance matrix

arXiv

引用

arXiv 2017年

作者： Wu, Xiaohuan Zhu, Wei-Ping Yan, Jun Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing China Department of Electrical and Computer Engineering Concordia University Montreal Canada

The atomic norm minimization (ANM) has been successfully incorporated into the two-dimensional (2-D) direction-ofarrival (DOA) estimation problem for super-resolution. However, its computational workload might be unaffordable when the number of snapshots is large. In this paper, we propose two gridless methods for 2-D DOA estimation with L-shaped array based on the atomic norm to improve the computational efficiency. Firstly, by exploiting the cross-covariance matrix an ANM-based model has been proposed. We then prove that this model can be efficiently solved as a semi-definite programming (SDP). Secondly, a modified model has been presented to improve the estimation accuracy. It is shown that our proposed methods can be applied to both uniform and sparse L-shaped arrays and do not require any knowledge of the number of sources. Furthermore, since our methods greatly reduce the model size as compared to the conventional ANM method, and thus are much more efficient. Simulations results are provided to demonstrate the advantage of our methods. Copyright © 2017, The Authors. All rights reserved.

关键词： Computational efficiency

来源：评论

学校读者我要写书评

暂无评论

Direction-of-arrival estimation based on Toeplitz covariance matrix reconstruction

Direction-of-arrival estimation based on Toeplitz covariance...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Xiaohuan Wu Wei-Ping Zhu Jun Yan Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing China Department of Electrical and Computer Engineering Concordia University Montreal Canada

ISBN: (纸本)9781479999897

This paper addresses the issue of direction-of-arrival (DOA) estimation with an objective to eliminate the off-grid effect of the sparsity-based methods and enlarge the maximum number of distinguishable signals in the subspace-based methods. We first reconstruct the covariance matrix of the array output in the Toeplitz structure and then employ the reconstructed covariance matrix together with root-MUSIC to estimate the DOAs. The proposed covariance matrix reconstruction approach (CMRA) can be used for uniform and sparse linear arrays. It can also estimate the DOAs of multiple signals that are larger than the number of sensors by taking advantage of the array geometry. In contrast to the sparsity-based methods, CMRA is formulated in the continuous angle space rather than the discretized one, and hence it is immune to the off-grid effect. Simulations are carried out to verify the effectiveness of our method.

关键词： Covariance matrices Direction-of-arrival estimation Estimation Sensor arrays Minimization Eigenvalues and eigenfunctions Geometry

来源：评论

学校读者我要写书评

暂无评论

Research of Malicious Code Attack Effect Based on Synthetic Entropy Method

引用

Chinese Journal of Electronics 2023年第3期22卷 449-454页

作者： LI Peng WANG Ruchuan College of Computer Nanjing University of Posts and Telecommunications Nanjing China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing China Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education Jiangsu Province Nanjing China

To resolve the problem of assessing the effect of a network attack, this paper combines cross entropy with network character entropy method and proposes scheme to evaluate the malicious code attack effect. It captures the related indicators in real time and normalizes the data so as to evaluate it at the same level. It adopts cross entropy method to pretreat the indicators adaptively. We calculate the weight coefficient and exploit network character entropy method to evaluate the attack with accuracy according to the importance of the indicators in the evaluation system. Experimental results and corresponding comparisons reveal that the proposed method can quantitatively determine the exact effect of the malicious code attack.

关键词： Industries Medical services Entropy Malware Real-time systems Information technology

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：