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48th IEEE International Conference on Acoustics, Speech and Signal processing, ICASSP 2023

作者： Dai, Mingliang Huang, Zhizhong Gao, Jiaqi Shan, Hongming Zhang, Junping School of Computer Science Shanghai Key Lab of Intelligent Information Processing China Fudan University Institute of Science and Technology for Brain-inspired Intelligence Shanghai200433 China

ISBN: (纸本)9781728163277

Noisy annotations such as missing annotations and location shifts often exist in crowd counting datasets due to multi-scale head sizes, high occlusion, etc. These noisy annotations severely affect the model training, especially for density map-based methods. To alleviate the negative impact of noisy annotations, we propose a novel crowd counting model with one convolution head and one transformer head, in which these two heads can supervise each other in noisy areas, called Cross-Head Supervision. The resultant model, CHS-Net, can synergize different types of inductive biases for better counting. In addition, we develop a progressive cross-head supervision learning strategy to stabilize the training process and provide more reliable supervision. Extensive experimental results on Shang-haiTech and QNRF datasets demonstrate superior performance over state-of-the-art methods. Code is available at https://***/RaccoonDML/CHSNet. © 2023 IEEE.

关键词： Crowd counting noisy annotations

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Object-level saliency detection combining the contrast and spatial compactness hypothesis

Object-level saliency detection combining the contrast and s...

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2013 International Conference on Image processing, computer Vision, and Pattern Recognition, IPCV 2013, at WORLDCOMP 2013

作者： Zhang, Chi Wang, Weiqiang Liu, Xiaoqian School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China Key Lab of intelligence information Processing Institute of Computing Technology CAS Beijing China

ISBN: (纸本)1601322526

Object-level saliency detection is an important branch of visual saliency. Most previous methods are based on the contrast hypothesis which regards the regions presenting high contrast in a certain context as salient. Although the contrast hypothesis is valid in many cases, it can’t handle some difficult cases, especially when the salient object is large. To make up for the deficiencies of contrast hypothesis, we incorporate a novel spatial compactness hypothesis which can effectively handle those tough cases. In addition, we propose a unified framework which integrates multiple saliency maps generated on different feature maps built on different hypotheses. Our algorithm can automatically select saliency maps of high quality according to the quality evaluation score defined in this paper. The experimental results demonstrate that each key component of our method contributes to the final performance and the full version of our method outperforms all state-of-the-art methods on the most popular dataset. © 2013 CSREA Press. All rights reserved.

关键词： Object detection

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Motion-Aware Video Paragraph Captioning via Exploring Object-Centered Internal Knowledge 48

Motion-Aware Video Paragraph Captioning via Exploring Object...

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48th IEEE International Conference on Acoustics, Speech and Signal processing, ICASSP 2023

作者： Hu, Yimin Yu, Guorui Zhang, Yuejie Feng, Rui Zhang, Tao Lu, Xuequan Gao, Shang Fudan University School of Computer Science Shanghai Key Lab of Intelligent Information Processing China Shanghai University of Finance and Economics School of Information Management and Engineering China Deakin University School of Information Technology Australia

ISBN: (纸本)9781728163277

Video paragraph captioning task aims at generating a fine-grained, coherent and relevant paragraph for a video. Different from the images where objects are static, the temporal states of objects are changing in videos. The dynamic information could be contributed to understanding the whole video content. Existing works rarely put focus on modeling the dynamic changing state of the objects in the videos, causing the activities occurred in videos are poorly or wrongly depicted in paragraphs. To address this problem, we propose a novel Object State Tracking Network, which can capture the temporal state change of objects. However, due to the similarity of the consecutive frames in the videos, the information of the video is redundant and noisy. We further propose a semantic alignment mechanism, and enable the sentence information to refine the visual information. Extensive experiments on ActivityNet Captions demonstrate the effectiveness of our method. © 2023 IEEE.

关键词： Semantics

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Pyramid: Building Incentive Architecture for Unstructured Peer-to-Peer Network

Pyramid: Building Incentive Architecture for Unstructured Pe...

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Advanced International Conference on Telecommunications (AICT)

作者： Jia Zhao Jian-De Lu Jiangsu Key Laboratory of Computer Information Processing Technology Soochow University Suzhou Jiangsu China

As non-cooperation behaviors such as free-riding do not seems to have been checked according to a recent survey of Gnutella network [3], it hereby calls for more attention to this issue and more efforts in our future research to protect P2P networks. This paper presents a new incentive architecture- "Pyramid", whose idea first came out as a sales mode named "Pyramid Selling". By introducing this concept into P2P research, we believe the "magic" of encouraging sales in reality could also benefit the P2P world on encouraging cooperation. In particular, the paper describes in details the three layers of Pyramid’s hierarchical structure: fundamental infrastructure managing the peer organization and basic utilities, trade-based credit system supporting trust management and service charge and pyramid incentive mechanism encouraging cooperation of rational users. Model evaluation and discussion of the proposed pyramid incentive mechanism demonstrate its effectiveness in encouraging cooperation and discouraging non-cooperation respectively.

关键词： Buildings Peer to peer computing Marketing and sales computer architecture laboratories computer networks information processing Protection Degradation Recruitment

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Motion Matters: A Novel Motion Modeling for Cross-View Gait Feature Learning 48

Motion Matters: A Novel Motion Modeling for Cross-View Gait ...

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48th IEEE International Conference on Acoustics, Speech and Signal processing, ICASSP 2023

作者： Li, Jingqi Gao, Jiaqi Zhang, Yuzhen Shan, Hongming Zhang, Junping School of Computer Science Shanghai Key Lab of Intelligent Information Processing China Institute of Science and Technology for Brain-inspired Intelligence Fudan University Shanghai200433 China

ISBN: (纸本)9781728163277

As a unique biometric that can be perceived at a distance, gait has broad applications in person authentication, social security and so on. Existing gait recognition methods suffer from changes in viewpoint and clothing and barely consider extracting diverse motion features, a fundamental characteristic in gaits, from gait sequences. This paper proposes a novel motion modeling method to extract the discriminative and robust representation. Specifically, we first extract the motion features from the encoded motion sequences in the shallow layer. Then we continuously enhance the motion feature in deep layers. This motion modeling approach is independent of mainstream work in building network architectures. As a result, one can apply this motion modeling method to any backbone to improve gait recognition performance. In this paper, we combine motion modeling with one commonly used backbone (GaitGL) as GaitGL-M to illustrate motion modeling. Extensive experimental results on two commonly-used crossview gait datasets demonstrate the superior performance of GaitGL-M over existing state-of-the-art methods. © 2023 IEEE.

关键词： Network architecture

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Video Captioning via Relation-Aware Graph Learning 48

Video Captioning via Relation-Aware Graph Learning

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48th IEEE International Conference on Acoustics, Speech and Signal processing, ICASSP 2023

作者： Zheng, Yi Jing, Heming Xie, Qiujie Zhang, Yuejie Feng, Rui Zhang, Tao Gao, Shang Fudan University School of Computer Science Shanghai Key Lab of Intelligent Information Processing China Shanghai University of Finance and Economics School of Information Management and Engineering China Deakin University School of Information Technology Australia

ISBN: (纸本)9781728163277

Recent neural models for video captioning usually employed an encoder-decoder framework. However, most approaches either neglected the spatial and temporal interactions between objects in a video or implicitly modelled the interactions, resulting in less desired performance. In this paper, we propose a novel relation-aware graph learning framework. It explicitly models both spatial and temporal relations for objects. In particular, a relation-aware graph is designed to depict the spatial relations between different objects in a scene. Parallelly, a temporal graph network is designed to perform relational reasoning for the same objects in adjacent frames. Features of both types of relations are learned and fused for the follow-up language decoder. Experiments on two bench-mark datasets show the effectiveness of our framework. It achieves state-of-the-art performance with CIDEr scores on MSVD and MSR-VTT. © 2023 IEEE.

关键词： Relation-Aware Graph Scene Graph Temporal Graph Video captioning

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IMEWAS--A Integrated Multi-platform EAPoW-Based WLAN AAA Solution

IMEWAS--A Integrated Multi-platform EAPoW-Based WLAN AAA Sol...

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International Conference on Wireless and Mobile Communications (ICWMC)

作者： Ling Chen Jian-de Lu Jiangsu Key Laboratory of Computer Information Processing Technology Soochow University Suzhou Jiangsu China

ISBN: (纸本)9781424431397;9780769527963

As security is becoming a significant obstacle to wider deployment of wireless LANs, IEEE 802.1x and EAPoW has been put forward to enhance authentication in WLAN. At present, some existing client solution such as Xsupplicant or WIRE1x has only applies to one platform, Linux or Windows, and is ill-considered of EAPoW. This paper discusses an integrated multi- platform EAPOW-based WLAN AAA Solution - IMEWAS, its architecture and module design and implementation. The integrated flexible and secure solution has been proved feasible.

关键词： Wireless LAN Authentication Access protocols Network servers Linux Wireless application protocol Access control Encapsulation File servers Authorization

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A Real-time Cutting Model Based on Finite Element and Order Reduction

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computer Systems Science & Engineering 2022年第10期43卷 1-15页

作者： Xiaorui Zhang Wenzheng Zhang Wei Sun Hailun Wu Aiguo Song Sunil Kumar Jha Wuxi Research Institute Nanjing University of Information Science&TechnologyWuxi214100China Engineering Research Center of Digital Forensics Ministry of EducationJiangsu Engineering Center of Network MonitoringSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China School of Automation Nanjing University of Information Science&TechnologyNanjing210044China State Key Laboratory of Bioelectronics Jiangsu Key Lab of Remote Measurement and ControlSchool of Instrument Science and EngineeringSoutheast UniversityNanjing210096China IT Fundamentals and Education Technologies Applications University of Information Technology and Management in RzeszowRzeszow Voivodeship100031Poland

Telemedicine plays an important role in Corona Virus Disease 2019(COVID-19).The virtual surgery simulation system,as a key component in telemedicine,requires to compute in ***,this paper proposes a realtime cutting model based on finite element and order reduction method,which improves the computational speed and ensure the real-time *** proposed model uses the finite element model to construct a deformation model of the virtual ***,a model order reduction method combining proper orthogonal decomposition and Galerkin projection is employed to reduce the amount of deformation *** addition,the cutting path is formed according to the collision intersection position of the surgical instrument and the lesion area of the virtual ***,the Bezier curve is adopted to draw the incision outline after the virtual lung has been ***,the simulation system is set up on the PHANTOM OMNI force haptic feedback device to realize the cutting simulation of the virtual *** results show that the proposed model can enhance the real-time performance of telemedicine,reduce the complexity of the cutting simulation and make the incision smoother and more natural.

关键词： Virtual surgery cutting model finite element model model order reduction Bezier curve

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Data distribution algorithm of high-speed intrusion detection system based on network processor

Data distribution algorithm of high-speed intrusion detectio...

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2nd International Conference on Semantics, Knowledge, and Grid, SKG 2006

作者： Xu, Cheng Yu, Fei Dai, Zhenghui Yue, Guangxue Li, Renfa School of Computer and Communication Hunan University Changsha 410082 China Provincial Key Laboratory of Computer Information Processing Technology Jiangsu Province Suzhou Jiangsu 2150063 China State Key Laboratory of Information Security Graduate School Chinese Academy of Sciences Beijing 100049 China College of Informationg Engineering JiaXing University JiaXing 314000 China

ISBN: (纸本)076952673X

Because the processing speed of intrusion detection system can hardly keep pace with the high-speed development of network, improving the speed of intrusion detection has been the problem starved for solve. By adopting the network processor, a distribution algorithm based on protocol analysis has been realized. By delivering the captured data package to each detect node according to protocol types and then accomplishing the detection for data package through the collaboration of the detect nodes, the processing efficiency of the intrusion detection system has been improved as a whole. © 2006 IEEE.

关键词： Intrusion detection

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Dynamic thresholding networks for schizophrenia diagnosis

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Artificial Intelligence in Medicine 2019年 96卷 25-32页

作者： Zou, Hongliang Yang, Jian PCA Lab Key Lab of Intelligent Perception and systems for High-Dimensional Information of Ministry of Education Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing 210094 China

Background and objective: Functional connectivity (FC) based on resting-state functional magnetic resonance imaging (rs-fMRI) is an effective approach to describe the neural interaction between distributed brain regions. Recent progress in neuroimaging study reported that the connection between regions is time-varying, which may enhance understanding of normal cognition and alterations that result from brain disorders. However, conventional sliding window based dynamic FC (DFC) analysis has several drawbacks, including arbitrary choice of window length, inaccurate descriptor of FC, and the fact that many spurious connections were included in the fully-connected networks due to noise. This study aims to develop an effective dynamic thresholding brain networks method to diagnose schizophrenia. Methods: In this study, we proposed a time-varying window length DFC method based on dynamic time warping to construct brain functional networks. To further eliminate the influence of spurious connections caused by noise, orthogonal minimum spanning tree was applied in these networks to generate time-varying window length dynamic thresholding FC (TVWDTFC) networks. To validate the effectiveness of our proposed method, experiments were conducted on a dataset, which including 56 individuals with schizophrenia and 74 healthy controls. Results: We achieved a classification accuracy of 0.8077 (p < 0.001, permutation test) using support vector machine. Experimental results demonstrated that the proposed method outperforms several state-of-the-art approaches, which verified the effectiveness of our proposed TVWDTFC method in schizophrenia diagnosis. Additionally, we also found that the selected discriminative features were mostly distributed in frontal, parietal, and limbic area. Conclusions: The results suggest that our approach may be a promising tool for computer-aided diagnosis of schizophrenia. © 2019 Elsevier B.V.

关键词： Dynamic time warping Orthogonal minimum spanning tree rs-fMRI Schizophrenia Time-varying window length DFC

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