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作者： Cerda, Mauricio Valenzuela, Renato Hitschfeld-Kahler, Nancy Terissi, Lucas D. Gómez, Juan C. INRIA-Loria Nancy Grand Est Equipe Cortex - Bat. C040 54506 Vandoeuvre-les-Nancy France Department of Computer Science Universidad de Chile Blanco Encalada 2120 Santiago Chile Laboratory for System Dynamics and Signal Processing Universidad Nacional de Rosario CONICET Rosario Argentina

ISBN: (纸本)9780769544007

In computer vision, the animation of objects has attracted a lot of attention, specially the animations of 3D face models. The animation of face models requires in general to manually adapt each generic movement (open/close mouth) to each specific head geometry. In this work we propose a technique for the animation of any face model avoiding most of the manual intervention. In order to achieve this we assume that: (1) faces, despite obvious differences are quite similar and a single generic model can be used to simplify deformations and (2) using this face model, a simple interpolation technique can be used, with minimal manual intervention. Several examples are presented to verify the realism of the obtained animations. © 2010 IEEE.

关键词： Animation

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Design of multiple anti-windup loops for multiple activations

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science China(Information sciences) 2012年第9期55卷 1925-1934页

作者： WU XiongJun 1,2 & LIN Zongli 3,1 1 department of Automation,Shanghai Jiao Tong University,and Key laboratory of system Control and Information processing,Ministry of Education of China,Shanghai 200240,China 2 No.802 Institute of Shanghai Academy of Space Flight Technology,the Eighth Academy of China Aerospace science and Technology Corporation,Shanghai 200090,China 3 Charles L.Brown department of Electrical and computer Engineering,University of Virginia,P.O.Box 400743,Charlottesville,VA 22904-4743,USA 1. Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China2. No. 802 Institute of Shanghai Academy of Space Flight Technology the Eighth Academy of China Aerospace Science and Technology Corporation Shanghai 200090 China3. Charles L. Brown Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 Charlottesville VA 22904-4743 USA

This paper considers anti-windup design for linear systems subject to actuator *** anti-windup gains are designed for activations immediately at the occurrence actuator saturation,after the saturation has reached a certain level and in anticipation of the occurrence of saturation,*** design is based on the minimization of L 2 gain from the disturbance to the controlled output of the resulting closed-loop *** anti-windup scheme involves a single anti-windup loop for immediate activation.A recent innovation is to design a single anti-windup loop for delayed or anticipatory activation,as well as to design two anti-windup gains,one for immediate activation and one for delayed *** design of three anti-windup gains for three different activations is shown through simulation to lead to significant further performance improvement over the previous activation schemes.

关键词： actuator saturation anti-windup anticipatory activation delayed activation L 2 gain nonlinear control

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Evidence-based treatment of medical guideline

Communications in Computer and Information Science

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Communications in computer and Information science 2014年 480卷 185-197页

作者： Tian, Pingfang Zhu, Zhonghua Huang, Zhisheng College of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Realtime Industrial System Wuhan430065 China Department of Computer Science Vrije University of Amsterdam AmsterdamHV1081 Netherlands

Medical guidelines are recommendations on the appropriate treatment and care of people with specific diseases and conditions. Evidence-based medical guidelines are the document or recommendations which have been annotated with their relevant medical evidences, namely research findings from medical publications. We have observed the fact that there exist significant amount of medical guidelines have not yet annotated with relevant medical evidences, which becomes even more serious in the Chinese medical guidelines. In this paper, we propose an approach of evidence process of medical guidelines, such that we can find relevant evidences for those non-evidence-based medical guidelines. We develop a system called Link2Pubmed, which can retrieve the text which is described with a natural language and get the corresponding medical evidences. We use the word segmentation and part-of-speech tagging tools in natural language processing (NLP) to extract the keywords, and then translate them into corresponding English concepts in SNOMED CT, a well-known medical ontology. This system is an attempt to solve the existing problems in Chinese medical guidelines, which lack the annotations of relevant evidences. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Natural language processing systems

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A mathematical model, heuristic, and simulation study for a basic data staging problem in a heterogeneous networking environment

A mathematical model, heuristic, and simulation study for a ...

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Heterogeneous Computing Workshop

作者： Min Tan M.D. Theys H.J. Siegel N.B. Beck M. Jurczyk Cisco Systems Inc. San Jose CA USA Parallel Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Department of Computer Engineering and Computer Science University of Missouri Columbia Columbia MO USA

Data staging is an important data management problem for a distributed heterogeneous networking environment, where each data storage location and intermediate node may have specific data available, storage limitations, and communication links. Sites in the network request data items and each item is associated with a specific deadline and priority. It is assumed that not all requests can be satisfied by their deadline. The work concentrates on solving a basic version of the data staging problem in which all parameter values for the communication system and the data request information represent the best known information collected so far and stay fixed throughout the scheduling process. A mathematical model for the basic data staging problem is introduced. Then, a multiple-source shortest-path algorithm based heuristic for finding a suboptimal schedule of the communication steps for data staging is presented. A simulation study is provided, which evaluates the performance of the proposed heuristic. The results show the advantages of the proposed heuristic over two random based scheduling techniques. This research, based on the simplified static model, serves as a necessary step toward solving the more realistic and complicated version of the data staging problem involving dynamic scheduling, fault tolerance, and determining where to stage data.

关键词： Mathematical model computer networks Distributed computing Data engineering Military computing Intelligent networks computer network management Environmental management Memory Satellite broadcasting

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Meta-ZSDETR: Zero-shot DETR with Meta-learning

arXiv

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arXiv 2023年

作者： Zhang, Lu Zhang, Chenbo Zhao, Jiajia Guan, Jihong Zhou, Shuigeng Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory China Department of Computer Science & Technology Tongji University China

Zero-shot object detection aims to localize and recognize objects of unseen classes. Most of existing works face two problems: the low recall of RPN in unseen classes and the confusion of unseen classes with background. In this paper, we present the first method that combines DETR and meta-learning to perform zero-shot object detection, named Meta-ZSDETR, where model training is formalized as an individual episode based meta-learning task. Different from Faster R-CNN based methods that firstly generate class-agnostic proposals, and then classify them with visual-semantic alignment module, Meta-ZSDETR directly predict class-specific boxes with class-specific queries and further filter them with the predicted accuracy from classification head. The model is optimized with meta-contrastive learning, which contains a regression head to generate the coordinates of class-specific boxes, a classification head to predict the accuracy of generated boxes, and a contrastive head that utilizes the proposed contrastive-reconstruction loss to further separate different classes in visual space. We conduct extensive experiments on two benchmark datasets MS COCO and PASCAL VOC. Experimental results show that our method outperforms the existing ZSD methods by a large margin. Copyright © 2023, The Authors. All rights reserved.

关键词： Object detection

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Deep learning-based activity recognition and fine motor identification using 2D skeletons of cynomolgus monkeys

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Zoological Research 2023年第5期44卷 967-980页

作者： Chuxi Li Zifan Xiao Yerong Li Zhinan Chen Xun Ji Yiqun Liu Shufei Feng Zhen Zhang Kaiming Zhang Jianfeng Feng Trevor W.Robbins Shisheng Xiong Yongchang Chen Xiao Xiao School of Information Science and Technology Micro Nano System Center Fudan UniversityShanghai 200433China Department of Anesthesiology Huashan HospitalKey Laboratory of Computational Neuroscience and Brain-Inspired IntelligenceMinistry of EducationBehavioral and Cognitive Neuroscience CenterInstitute of Science and Technology for Brain-Inspired IntelligenceMOE Frontiers Center for Brain ScienceFudan UniversityShanghai 200433China Kuang Yaming Honors School Nanjing UniversityNanjingJiangsu 210023China Shanghai Key Laboratory of Intelligent Information Processing School of Computer ScienceFudan UniversityShanghai 200433China State Key Laboratory of Primate Biomedical Research Institute of Primate Translational MedicineKunming University of Science and TechnologyKunmingYunnan 650500China New Vision World LLC. Aliso ViejoCalifornia 92656USA Behavioural and Clinical Neuroscience Institute University of CambridgeCambridgeCB21TNUK

Video-based action recognition is becoming a vital tool in clinical research and neuroscientific study for disorder detection and ***,action recognition currently used in non-human primate(NHP)research relies heavily on intense manual labor and lacks standardized *** this work,we established two standard benchmark datasets of NHPs in the laboratory:Monkeyin Lab(Mi L),which includes 13 categories of actions and postures,and MiL2D,which includes sequences of two-dimensional(2D)skeleton ***,based on recent methodological advances in deep learning and skeleton visualization,we introduced the Monkey Monitor Kit(Mon Kit)toolbox for automatic action recognition,posture estimation,and identification of fine motor activity in *** the datasets and Mon Kit,we evaluated the daily behaviors of wild-type cynomolgus monkeys within their home cages and experimental environments and compared these observations with the behaviors exhibited by cynomolgus monkeys possessing mutations in the MECP2 gene as a disease model of Rett syndrome(RTT).Mon Kit was used to assess motor function,stereotyped behaviors,and depressive phenotypes,with the outcomes compared with human manual *** Kit established consistent criteria for identifying behavior in NHPs with high accuracy and efficiency,thus providing a novel and comprehensive tool for assessing phenotypic behavior in monkeys.

关键词： Action recognition Fine motor identification Two-stream deep model 2D skeleton Non-human primates Rett syndrome

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Meta-ZSDETR: Zero-shot DETR with Meta-learning

Meta-ZSDETR: Zero-shot DETR with Meta-learning

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International Conference on computer Vision (ICCV)

作者： Lu Zhang Chenbo Zhang Jiajia Zhao Jihong Guan Shuigeng Zhou Shanghai Key Lab of Intelligent Information Processing and School of Computer Science Fudan University China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory China Department of Computer Science & Technology Tongji University China

关键词：

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Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive Learning 24

Towards High-resolution 3D Anomaly Detection via Group-Level...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Zhu, Hongze Xie, Guoyang Hou, Chengbin Dai, Tao Gao, Can Wang, Jinbao Shen, Linlin National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China Department of Computer Science City University of Hong Kong Hong Kong Hong Kong Department of Intelligent Manufacturing CATL Ningde China Fuzhou Fuyao Institute for Advanced Study Fuyao University of Science and Technology Fuzhou China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Guangdong Provincial Key Laboratory of Intelligent Information Processing Shenzhen China Shenzhen University Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China

ISBN: (纸本)9798400706868

High-resolution point clouds (HRPCD) anomaly detection (AD) plays a critical role in precision machining and high-end equipment manufacturing. Despite considerable 3D-AD methods that have been proposed recently, they still cannot meet the requirements of the HRPCD-AD task. There are several challenges: i) It is difficult to directly capture HRPCD information due to large amounts of points at the sample level;ii) The advanced transformer-based methods usually obtain anisotropic features, leading to degradation of the representation;iii) The proportion of abnormal areas is very small, which makes it difficult to characterize. To address these challenges, we propose a novel group-level feature-based network, called Group3AD, which has a significantly efficient representation ability. First, we design an Intercluster Uniformity Network (IUN) to present the mapping of different groups in the feature space as several clusters, and obtain a more uniform distribution between clusters representing different parts of the point clouds in the feature space. Then, an Intracluster Alignment Network (IAN) is designed to encourage groups within the cluster to be distributed tightly in the feature space. In addition, we propose an Adaptive Group-Center Selection (AGCS) based on geometric information to improve the pixel density of potential anomalous regions during inference. The experimental results verify the effectiveness of our proposed Group3AD, which surpasses Reg3D-AD by the margin of 5% in terms of object-level AUROC on Real3D-AD. We provide the code and supplementary information on our website: https://***/M-3LAB/Group3AD. © 2024 ACM.

关键词： Contrastive Learning

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Abstraction-Based Verification of Approximate Pre-Opacity for Control systems

arXiv

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arXiv 2022年

作者： Hou, Junyao Liu, Siyuan Yin, Xiang Zamani, Majid Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University China Department of Electrical and Computer Engineering Technical University of Munich Germany Department of Computer Science LMU Munich Germany Department of Computer Science University of Colorado Boulder United States

In this paper, we consider the problem of verifying pre-opacity for discrete-time control systems. Preopacity is an important information-flow security property that secures the intention of a system to execute some secret behaviors in the future. Existing works on pre-opacity only consider non-metric discrete systems, where it is assumed that intruders can distinguish different output behaviors precisely. However, for continuous-space control systems whose output sets are equipped with metrics (which is the case for most real-world applications), it is too restrictive to assume precise measurements from outside observers. In this paper, we first introduce a concept of approximate pre-opacity by capturing the security level of control systems with respect to the measurement precision of the intruder. Based on this new notion of pre-opacity, we propose a verification approach for continuous-space control systems by leveraging abstraction-based techniques. In particular, a new concept of approximate pre-opacity preserving simulation relation is introduced to characterize the distance between two systems in terms of preserving pre-opacity. This new system relation allows us to verify pre-opacity of complex continuous-space control systems using their finite abstractions. We also present a method to construct pre-opacity preserving finite abstractions for a class of discrete-time control systems under certain stability assumptions. Copyright © 2022, The Authors. All rights reserved.

关键词： Opacity

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Visual tracking via an ensemble of random classifiers

Visual tracking via an ensemble of random classifiers

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Yichun Shi Hesheng Wang Department of Computer Science Shanghai Jiao Tong University Shanghai China Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Shanghai China

ISBN: (纸本)9781467389600

One largest problem for tracking-by-detection methods is the incomplete and noisy training set. Occlusion, illumination and many other problems could lead to this problem. Models that are not adaptive enough would fail to track the target when drastic appearance change takes place. Adaptive ones, although keep tracking at first, could lose the target because of learning too many incorrect samples. In this paper, we present an ensemble model of random classifiers updated on different dataset. When the appearance of the target changes drastically and some sub-models are confused, the others could help correct the tracking result. A latent variable is added for choosing sub-models and it naturally leads to predicting the new samples with a weighted sum of sub-models. To calculate the weight, we add a generative model to each random classifier. Experiments show that our method could track the target robustly and accurately.

关键词： Target tracking Training Visualization Noise measurement Robustness Lighting Adaptation models

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