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检索条件"任意字段=6th International Workshop on Graph-Based Representations in Pattern Recognition"

共 215 条记录，以下是151-160 订阅

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Improved Accuracy for Automated Communication pattern Characterization Using Communication graphs and Aggressive Search Space Pruning 6th

Improved Accuracy for Automated Communication Pattern Charac...

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6th international workshop on Extreme-Scale Programming Tools (ESPT)

作者： Roth, Philip C. Oak Ridge Natl Lab Oak Ridge TN 37831 USA

ISBN: (纸本)9783030178727;9783030178710

An understanding of a parallel application's communication behavior is useful for a range of activities including debugging and optimization, job scheduling, target system selection, and system design. Because it can be challenging to understand communication behavior, especially for those who lack expertise or who are not familiar with the application, I and two colleagues recently developed an automated, search-based approach for recognizing and parameterizing application communication behavior using a library of common communication patterns. this initial approach was effective for characterizing the behavior of many workloads, but I identified some combinations of communication patterns for which the method was inefficient or would fail. In this paper, I discuss one such troublesome pattern combination and propose modifications to the recognition method to handle it. Specifically, I propose an alternative approach that uses communication graphs instead of traditional communication matrices to improve recognition accuracy for collective communication operations, and that uses a non-greedy recognition technique to avoid search space dead-ends that trap the original greedy recognition approach. My modified approach uses aggressive search space pruning and heuristics to control the potential for state explosion caused by its non-greedy pattern recognition method. I demonstrate the improved recognition accuracy and pruning efficacy of the modified approach using several synthetic and real-world communication pattern combinations.

关键词： Heuristic methods

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Wildlife net-gamekeepers using sensor network 07

Wildlife net-gamekeepers using sensor network

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6th ACM SIGCOMM workshop on Network and System Support for Games, NetGames '07

作者： Trejos, Leonardo M. Kamada, Masaru Yonekura, Tatsuhiro Reaz, Mamun Bin Ibne Ibaraki University 4-12-1 Nakanarusawa Hitachi ibaraki 316-8511 Japan Department of Electrical and Computer Engineering International Islamic University Malaysia Jalan Gombak 53100 Kuala Lumpur Malaysia

ISBN: (纸本)9780980446005

Wildlife lies in vast and wide areas where human gamekeepers work as protectors. the task of recognizing poachers in protected areas is tedious, tiring, and requires huge manpower and computational overhead. A fully automated system cannot accurately identify every such poacher. this paper proposes a conceptual system based on sensor network, which will provide amusement for cyberspace gamekeepers while protecting the wildlife. For this, the sensory data from the park is mapped to a game-like virtual environment. Cyberspace gamekeepers will access the system and play the game. While playing, they will help to conserve the wildlife in national parks by pattern recognition of intruders in the game. the sensor network in the proposed system will use microphone, accelerometers and wireless transmission system.

关键词： Conservation

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graph matching using spectral seriation and string edit distance

Graph matching using spectral seriation and string edit dist...

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4th IAPR international workshop on graph based representations in pattern recognition, GbRPR 2003

作者： Robles-Kelly, Antonio Hancock, Edwin R. Department of Computer Science University of York YorkY01 5DD United Kingdom

ISBN: (纸本)354040452X

this paper is concerned with computing graph edit distance. One of the criticisms that can be leveled at existing methods for computing graph edit distance is that it lacks the formality and rigour of the computation of string edit distance. Hence, our aim is to convert graphs to string sequences so that string matching techniques can be used. To do this we use graph spectral seriation method to convert the adjacency matrix into a string or sequence order. We show how the serial ordering can be established using the leading eigenvector of the graph adjacency matrix. We pose the problem of graph-matching as maximum a posteriori probability alignment of the seriation sequences for pairs of graphs. this treatment leads to an expression in which for edit cost is the negative logarithm of the a posteriori sequence alignment probability. To compute the string alignment probability we provide models of the edge compatibility error and the probability of individual node correspondences. © Springer-Verlag Berlin Heidelberg 2003.

关键词： pattern matching

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A Comprehensive Mobility Management Solution for Handling Peak Load in Cellular Network Scenarios

A Comprehensive Mobility Management Solution for Handling Pe...

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6th ACM international workshop on Mobility Management and Wireless Access (MobiWac 2007)

作者： Michaelis, Stefan Lewandowski, Andreas Daniel, Kai Yousaf, Faqir Zarrar Wietfeld, Christian Dortmund Univ Technol CNI Dortmund Germany

ISBN: (纸本)9781605580555

First responders are suffering from insufficient information about the incident during alerting and operations at the scene itself. Particularly at major incident operations detailed and up-to-date multimedia information are indispensable and have to be provided as fast and reliable as possible to the rescue forces. thus, challenging requirements on the mobile communication system like traffic prioritization, seamless handover and everywhere connectivity arise front this use case. In this paper we present a holistic approach for a suitable heterogeneous communication architecture considering the complete mobility management process that consists of mobility modeling, handover trigger algorithms and IP-based handover protocols applied cm a big public event at, a stadium.

关键词： Mobility Model pattern recognition Handover Protocol

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Part-based high accuracy recognition of serial numbers in bank notes 6

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6th IAPR TC3 international workshop on Artificial Neural Networks for pattern recognition, ANNPR 2014

作者： Feng, Bo-Yuan Ren, Mingwu Zhang, Xu-Yao Suen, Ching Y. School of Computer Science Nanjing University of Science and Technology Nanjing210094 China National Laboratory of Pattern Recognition Institute of Automation of Chinese Academy of Sciences Beijing100190 China Centre for Pattern Recognition and Machine Intelligence Concordia University MontrealH3G 1M8 Canada

ISBN: (纸本)9783319116556

this paper proposes a novel part-based character recognition method for a new topic of RMB (renminbi bank note, the paper currency used in China) serial number recognition, which is important for reducing financial crime and improving financial market stability and social security. Given an input sample, we first generate a set of local image parts using the Difference-of-Gaussians (DoG) keypoint detector. then, all of the local parts are classified by an SVM classifier to provide a confidence vector for each part. Finally, three methods are introduced to combine the recognition results of all parts. Since the serial number samples suffer from complex background, occlusion, and degradation, our part-based method takes advantage of both global and local character structure features, and offers an overall increase in robustness and reliability to the entire recognition system. Experiments conducted on a RMB serial number character database show that the test accuracy boosted from 98.90% to 99.33% by utilizing the proposed method with multiple voting based combination strategy. the part-based recognition method can also be extended to other types of banknotes, such as Euro, U.S. and Canadian dollars, or in character recognition applications with complex backgrounds. © Springer international Publishing Switzerland 2014.

关键词： Character recognition

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Symbol recognition using bipartite transformation distance and angular distribution alignment

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6th international workshop on graphics recognition, GREC 2005

作者： Min, Feng Zhang, Wan Wenyin, Liu Department of Computer Science City University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9783540347118

In this paper, we present an integrated system for symbol recognition. the whole recognition procedure consists of image compression, denoising and recognition. We present a pixel-based method to calculate similarity between two symbols using the bipartite transformation distance after they are aligned by their angular distributions. the proposed method can overcome some shortcomings of other pixel-level methods. We also propose a new denoising technique in our system to improve the recognition precision and efficiency. Evaluation results on test sets provided by the 2nd IAPR contest on symbol recognition show good performance of the system in recognizing symbols with degradation and affine transformation. © Springer-Verlag Berlin Heidelberg 2006.

关键词： pattern recognition

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42nd German Conference on pattern recognition, DAGM GCPR 2020 held in parallel with 25th international Symposium on Vision, Modeling, and Visualization, VMV 2020 and 10th Eurographics workshop on Visual Computing for Biology and Medicine, VCBM 2020

42nd German Conference on Pattern Recognition, DAGM GCPR 202...

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42nd German Conference on pattern recognition, DAGM GCPR 2020 held in parallel with 25th international Symposium on Vision, Modeling, and Visualization, VMV 2020 and 10th Eurographics workshop on Visual Computing for Biology and Medicine, VCBM 2020

ISBN: (纸本)9783030712778

the proceedings contain 34 papers. the special focus in this conference is on pattern recognition. the topics include: Adversarial Synthesis of Human Pose from Text;long-Term Anticipation of Activities with Cycle Consistency;multi-stage Fusion for One-Click Segmentation;neural Architecture Performance Prediction Using graph Neural Networks;discovering Latent Classes for Semi-supervised Semantic Segmentation;Riemannian SOS-Polynomial Normalizing Flows;automated Water Segmentation and River Level Detection on Camera Images Using Transfer Learning;Does SGD Implicitly Optimize for Smoothness?;Looking Outside the Box: the Role of Context in Random Forest based Semantic Segmentation of PolSAR Images;semantic Bottlenecks: Quantifying and Improving Inspectability of Deep representations;haar Wavelet based Block Autoregressive Flows for Trajectories;center3D: Center-based Monocular 3D Object Detection with Joint Depth Understanding;constellation Codebooks for Reliable Vehicle Localization;towards Bounding-Box Free Panoptic Segmentation;proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks;unsupervised Part Discovery by Unsupervised Disentanglement;on the Lifted Multicut Polytope for Trees;conditional Invertible Neural Networks for Diverse Image-to-Image Translation;image Inpainting with Learnable Feature Imputation;4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving;bias Detection and Prediction of Mapping Errors in Camera Calibration;inline Double Layer Depth Estimation with Transparent Materials;a Differentiable Convolutional Distance Transform Layer for Improved Image Segmentation;PET-Guided Attention Network for Segmentation of Lung Tumors from PET/CT Images;self-supervised Disentanglement of Modality-Specific and Shared Factors Improves Multimodal Generative Models;multimodal Semantic Forecasting based on Conditional Generation of Future Features;learning to Identify Physical Parameters from Video Using Differentiable

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Depression Assessment by Fusing High and Low Level Features from Audio, Video, and Text 6

Depression Assessment by Fusing High and Low Level Features ...

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6th international workshop on Audio-Visual Emotion recognition Challenge - Depression, Mood, and Emotion (AVEC)

作者： Pampouchidou, Anastasia Pediaditis, Matthew Giannakakis, Georgios Marias, Kostas Simantiraki, Olympia Manousos, Dimitrios Meriaudeau, Fabrice Yang, Fan Fazlollahi, Amir Roniotis, Alexandros Simos, Panagiotis Tsiknakis, Manolis Univ Bourgogne Lab Elect Informat & Image Le Creusot France Fdn Res & Technol Hellas FORTH Inst Comp Sci Computat BioMed Lab Iraklion Crete Greece CSIRO Australian E Hlth Res Ctr Brisbane Qld Australia TEIC Biomed Informat & EHlth Lab Iraklion Crete Greece Univ Teknol Petronas CISIR Dept Elect Engn Teronoh Perek Malaysia Univ Crete Sch Med Div Psychiat Iraklion Crete Greece

ISBN: (纸本)9781450345163

Depression is a major cause of disability world-wide. the present paper reports on the results of our participation to the depression sub-challenge of the sixth Audio/Visual Emotion Challenge (AVEC 2016), which was designed to compare feature modalities ( audio, visual, interview transcript-based) in gender-based and gender-independent modes using a variety of classification algorithms. In our approach, both high and low level features were assessed in each modality. Audio features were extracted from the low-level descriptors provided by the challenge organizers. Several visual features were extracted and assessed including dynamic characteristics of facial elements (using Landmark Motion History Histograms and Landmark Motion Magnitude), global head motion, and eye blinks. these features were combined with statistically derived features from pre-extracted features ( emotions, action units, gaze, and pose). Both speech rate and word-level semantic content were also evaluated. Classification results are reported using four different classification schemes: i) gender-based models for each individual modality, ii) the feature fusion model, ii) the decision fusion model, and iv) the posterior probability classification model. Proposed approaches outperforming the reference classification accuracy include the one utilizing statistical descriptors of low-level audio features. this approach achieved f1-scores of 0.59 for identifying depressed and 0.87 for identifying notdepressed individuals on the development set and 0.52/0.81, respectively for the test set.

关键词： AVEC 2016 image processing speech processing pattern recognition affective computing depression assessment multimodal fusion

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Knowledge-Enriched Event Causality Identification via Latent Structure Induction Networks 59

Knowledge-Enriched Event Causality Identification via Latent...

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Joint Conference of 59th Annual Meeting of the Association-for-Computational-Linguistics (ACL) / 11th international Joint Conference on Natural Language Processing (IJCNLP) / 6th workshop on Representation Learning for NLP (RepL4NLP)

作者： Cao, Pengfei Zuo, Xinyu Chen, Yubo Liu, Kang Zhao, Jun Chen, Yuguang Peng, Weihua Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing Peoples R China Beijing Baidu Netcom Sci Technol Co Ltd Beijing Peoples R China

ISBN: (纸本)9781954085527

Identifying causal relations of events is an important task in natural language processing area. However, the task is very challenging, because event causality is usually expressed in diverse forms that often lack explicit causal clues. Existing methods cannot handle well the problem, especially in the condition of lacking training data. Nonetheless, humans can make a correct judgement based on their background knowledge, including descriptive knowledge and relational knowledge. Inspired by it, we propose a novel Latent Structure Induction Network (LSIN) to incorporate the external structural knowledge into this task. Specifically, to make use of the descriptive knowledge, we devise a Descriptive graph Induction module to obtain and encode the graph-structured descriptive knowledge. To leverage the relational knowledge, we propose a Relational graph Induction module which is able to automatically learn a reasoning structure for event causality reasoning. Experimental results on two widely used datasets indicate that our approach significantly outperforms previous state-of-the-art methods.

关键词： Natural language processing systems

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From equivalent weighting functions to equivalent contraction kernels

From equivalent weighting functions to equivalent contractio...

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6th international workshop on Digital Image Processing and Computer graphics (DIP-97): Applications in Humanities and Natural Sciences

作者： Kropatsch, Walter G. Vienna Univ. of Technology Inst. of Automation 183/2 Pattern Recognition + IP Grp. Treitlstr. 3 A-1040 Wien Austria

Burt introduced 1983 'equivalent weighting function': "Iterative pyramid generation is equivalent to convolving the image g0 with a set of 'equivalent weighting functions' hl:" gl = hl * g0 = h * gl-1, l > 1. It allowed him to study the effects of iterated reduction (e.g. the low-pass character of Gaussian pyramids) using the single parameter hl without giving up the efficient iterative computation. A similar concept applies to graph pyramids built by dual graph contraction. this new algorithm reduces the number of vertices and of edges of a pair of dual image graphs while, at the same time, the topological relations among the 'surviving' components are preserved. Repeated application produces a stack of successively smaller graphs: a pair of dual irregular pyramids. the process is controlled by selected decimation parameters which consist of a subset of surviving vertices and associated contraction kernels. these play a similar rote for graph pyramids than the convolution kernels of Gaussian pyramids. Equivalent contraction kernels (ECKs) combine two or more contraction kernels into one single contraction kernel which generates the same result in one single dual contraction. the basic concepts are elaborated and discussed. the new theory opens a large variety of possibilities to explore the domain of 'all' graph pyramids.

关键词： Image analysis

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