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A Comparison between Recursive Neural Networks and Graph Neural Networks

A Comparison between Recursive Neural Networks and Graph Neu...

引用

International Joint conference on Neural Networks (IJCNN)

作者： V. Di Massa G. Monfardini L. Sarti F. Scarselli M. Maggini M. Gori Dipartimento di Ingegneria dellInnovazione Università degli Studi di Siena Siena Italy

Recursive neural networks (RNNs) and graph neural networks (GNNs) are two connectionist models that can directly process graphs. RNNs and GNNs exploit a similar processing framework, but they can be applied to different input domains. RNNs require the input graphs to be directed and acyclic, whereas GNNs can process any kind of graphs. The aim of this paper consists in understanding whether such a difference affects the behaviour of the models on a real application. An experimental comparison on an image classification problem is presented, showing that GNNs outperforms RNNs. Moreover the main differences between the models are also discussed w.r.t. their input domains, their approximation capabilities and their learning algorithms.

关键词： Neural networks Recurrent neural networks Tree graphs Approximation algorithms Web pages Kernel computer vision Image classification pattern recognition Natural languages

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Determining shot assonance/dissonance via salience maps and the match frame principle of continuity editing

Determining shot assonance/dissonance via salience maps and ...

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International conference on Multimedia Modeling (MMM)

作者： R. Turetsky X. Halkias Department of Electrical Engineering Columbia University USA

One of the ultimate challenges of computer vision is in video semantic understanding. Many efforts at detecting events in video have focused on structured sequences such as sports or news broadcasts. However even in seemingly freeform media such as feature films, there is an inherent structure and established production codes. Over the last century, film theorists have developed the principles of continuity editing. One tenet of continuity editing is known as match framing; in order for a shot boundary to appear seamless, the viewer's focus of attention should not have to move very far from one shot to the next. Filmmakers generally adhere to the continuity editing guidelines in order for audiences to maintain their suspension of disbelief. Often times, however, prudent violations of continuity can jar the viewer, for example during action scenes or moments of high intensity. By detecting violations of the continuity editing principles, it is possible to locate portions of a film that the filmmaker is interested in portraying as different from the rest of the film. We have developed a method for automatically detecting violations of the match framing principle that fuses film theory, psychophysical modeling, and image morphology and pattern recognition. First, shot detection is performed on the entire film. Next, we compute the saliency map on a frame before and after the shot boundary. We then treat each saliency map as a distribution, and estimate a 3-component Gaussian mixture model of the salient peaks. Finally, by comparing distributions we are able to estimate how active the viewer's eye needs to be from one shot to the next. Experiments demonstrate a correlation between match frame violations and plot in a small corpus of full-length movies

关键词： computer vision Event detection Multimedia communication Broadcasting Production Focusing Guidelines Layout pattern matching Fuses

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Image Registration in Intra-oral Radiography

Image Registration in Intra-oral Radiography

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Annual International conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： C.C. Leung K.L. Yiu W.K. Tsui K.Y. Zee Department of Electrical & Electronic Engineering University of Hong Kong Hong Kong China Faculty of Dentistry University of Hong Kong Hong Kong China

Image registration is one of the image processing methods which is widely used in computer vision, pattern recognition, and medical imaging. In digital subtraction radiography, image registration is one of the important prerequisites to match the reference and subsequent images. In this paper, we propose an automatic non-rigid registration method namely curvature-based registration that relies on a curvature based penalizing term and its application on dental radiography. The regularizing term of this intensity-based registration approach provides affine linear transformation so that pre-registration step is no longer necessary. This leads to faster and more reliable solutions. The implementation of this approach is based on the numerical solution of the underlying Euler-Lagrange equations. In addition, a comparison between this algorithm and linear alignment method (LAM) with 20 image pairs is presented

关键词： Image registration Diagnostic radiography Dentistry Biomedical imaging Equations Application software Bone diseases Image processing computer vision Medical diagnostic imaging

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Health monitoring for damage initiation & progression during mechanical shock in electronic assemblies

Health monitoring for damage initiation & progression during...

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Electronic Components and Technology conference (ECTC)

作者： P. Lall P. Choudhary S. Gupte J. Suhling Department of Mechanical Engineering And Center for Advanced Vehicle Electronics Aubum University Auburn AL USA

Electronic products may be subjected shock and vibration during shipping, normal usage and accidental drop. High-strain rate transient bending produced by such loads may result in failure of fine-pitch electronics. Current experimental techniques rely on electrical resistance for determination of failure. Significant advantage can be gained by prior knowledge of impending failure for applications where the consequences of system failure may be catastrophic. This research effort focuses on an alternate approach to damage-quantification in electronic assemblies subjected to shock and vibration, without testing for electrical continuity. The proposed approach can be extended to monitor product-level damage. In this paper, statistical pattern recognition and leading indicators of shock-damage have been used to study the damage initiation and progression in shock and drop of electronic assemblies. Statistical pattern recognition is currently being employed in a variety of engineering and scientific disciplines such as biology, psychology, medicine, marketing, artificial intelligence, computer vision and remote sensing based in Jain, et. al. (2000). The application quantification of shock damage in electronic assemblies is new. Previously, free vibration of rectangular plates has been studied by various researchers as presented in Leissa (1969), Young (1950), Gorman (1982), Gurgoze (1984), and Wu (2003) for development of analytical closed-form models. In this paper, closed-form models have been developed for the eigen-frequencies and mode-shapes of electronic assemblies with various boundary conditions and component placement configurations. Model predictions have been validated with experimental data from modal analysis. Pristine configurations have been perturbed to quantify the degradation in confidence values with progression of damage. Sensitivity of leading indicators of shock-damage to subtle changes in boundary conditions, effective flexural rigidity, and transie

关键词： Electric shock Assembly Consumer electronics Condition monitoring Vibrations pattern recognition Boundary conditions Electric resistance Electronic equipment testing Engineering in medicine and biology

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Noise Clustering using a New Distance

Noise Clustering using a New Distance

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International conference on Information and Communication Technologies: From Theory to Applications, ICTTA

作者： Xiao-Hong Wu Jian-Jiang Zhou College of Information Science & Technology Nanjing University of Aeronautics and Astronautics Nanjing China College ofElectrical & Information Engineering Jiangsu University Zhenjiang China

Based on a new distance, a novel noise-resistant fuzzy clustering algorithm called alternative noise clustering (ANC) algorithm is proposed. ANC is an extension of the noise clustering (NC) algorithm proposed by Dave (1993). By replacing the Euclidean distance used in the objective function of NC algorithm, a new distance (non-Euclidean distance) is introduced in NC algorithm. Based on robust statistical point of view and influence function, the non-Euclidean distance is more robust than the Euclidean distance. So the ANC algorithm is more robust than the NC algorithm. Moreover, with the new distance ANC can deal with noises or outliers better than NC and fuzzy c-means (FCM). The better performance of the proposed algorithm is shown by performing experiments on data sets

关键词： Clustering algorithms Euclidean distance Noise robustness Partitioning algorithms Equations Educational institutions Space technology Digital images computer vision pattern recognition

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Driver's Head Pose Measurement and Corner Center Detection

Driver's Head Pose Measurement and Corner Center Detection

引用

SICE Annual conference

作者： Toshiki Matsui Naoki Suganuma Naofumi Fujiwara Graduate School of Natural Science & Technology Kanazawa University Ishikawa Japan

In this paper, we describe development of driver's head pose measurement and cornea center detection system. Similar researches have been performed so far. Most researches are based on feature point detection by the template matching. In general, the template matching has the weakness to the change in the expansion and contraction, rotation and brightness. To overcome these faults, three-dimensional shape alignment is introduced. Three-dimensional shape alignment is performed between driver's face model and shape data obtained in each time. Then, three-dimensional shapes are analyzed by stereovision. Moreover, shape alignment is performed by ICP registration. ICP registration can achieve high accuracy alignment, but needs huge computational effort, in general. To solve this problem, this paper introduces a reduction in volume of data based on pattern information in the image, coarse-to-fine search, and SIMD computing. Furthermore, this paper describes the cornea center estimation technique. At first, this technique extracts the eye region image from result of the head pose measurement. Afterward, the cornea center is estimated by recognition of eye contour and the ellipse fitting of cornea. It was confirmed by experiments that the proposed technique can measure in high accuracy, and the proposed technique is available in real environment

关键词： Head Cornea Measurement techniques Shape measurement Cameras computer vision Brightness Face detection Data mining Image processing

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IEEE computer Society conference on computer vision and pattern recognition workshops

IEEE Computer Society Conference on Computer Vision and Patt...

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2004 IEEE computer Society conference on computer vision and pattern recognition workshops, CVPRW 2004

The proceedings contain 186 papers. The topics discussed include: towards recovery of 3D chromosome structure;object-based visual 3D tracking of articulated objects via kinematic sets;non-rigid motion estimation and spatio-temporal realignment in FMRI;stochastic meta-descent for tracking articulated structures;gender recognition from walking movements using adaptive three-mode PCA;differential structure in non-linear image embedding functions;semantic-level understanding of human actions and interactions using event hierarchy;fusion of a multiple hypotheses color model and deformable contours for figure ground segmentation in dynamic environments;outlier rejection in deformable model tracking;spline-based motion recovery for 3D surfaces using nonrigid shape properties;and constraints for heterogeneous sensor auto-calibration.

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Examples of low-level computer vision on media processors

Examples of low-level computer vision on media processors

引用

2005 IEEE computer Society conference on computer vision and pattern recognition, CVPR 2005 - workshops

作者： Kisačanin, Branislav Delphi Corporation

ISBN: (纸本)0769526608

In this paper we describe a practical approach to processor selection for embedded computer vision applications. This approach is based on expected production volumes and other requirements. We then present several popular low-level computer vision techniques that have been algorithmically optimized for implementation on an emerging class of embedded architectures, media processors. © 2005 IEEE computer Society. All rights reserved.

关键词： computer architecture

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Boosting nearest neighbor classifiers for multiclass recognition

Boosting nearest neighbor classifiers for multiclass recogni...

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2005 IEEE computer Society conference on computer vision and pattern recognition, CVPR 2005 - workshops

作者： Athitsos, Vassilis Sclaroff, Stan Computer Science Department Boston University 111 Cummington Street BostonMA02215 United States

ISBN: (纸本)0769526608

Nearest neighbor classifiers are a popular method for multiclass recognition in a wide range of computer vision and pattern recognition domains. At the same time, the accuracy of nearest neighbor classifiers is sensitive to the choice of distance measure. This paper introduces an algorithm that uses boosting to learn a distance measure for multiclass k-nearest neighbor classification. Given a family of distance measures as input, AdaBoost is used to learn a weighted distance measure, that is a linear combination of the input measures. The proposed method can be seen both as a novel way to learn a distance measure from data, and as a novel way to apply boosting to multiclass recognition problems that does not require output codes. In our approach, multiclass recognition of objects is reduced to a single binary recognition task, defined on triples of objects. Preliminary experiments with eight UCI datasets yield no clear winner among our method, boosting using output codes, and k-nn classification using an unoptimized distance measure. Our algorithm did achieve lower error rates in some of the datasets, which indicates that it is a method worth considering for nearest neighbor recognition in various pattern recognition domains. © 2005 IEEE computer Society. All rights reserved.

关键词： Adaptive boosting

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Obstacle detection with stereo vision for off-road vehicle navigation

Obstacle detection with stereo vision for off-road vehicle n...

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2005 IEEE computer Society conference on computer vision and pattern recognition, CVPR 2005 - workshops

作者： Broggi, Alberto Caraffi, Claudio Fedriga, Rean Isabella Grisleri, Paolo Dipartimento di Ingegneria dell'Informazione Università di Parma ParmaI-43100 Italy

ISBN: (纸本)0769526608

In this paper we present an artificial vision algorithm for real-time obstacle detection in unstructured environments. The images have been taken using a stereoscopical vision system. The system uses a new approach, of low computational load, to calculate a V-disparity image between left and right corresponding images, in order to estimate the cameras pitch oscillation caused by the vehicle movement. Then, the obstacles are localized by stereo matching and mapped in real world coordinates. Experimental results on sequences taken from a moving vehicle (which partecipated to the DARPA Grand Challenge 2004) in different unstructured scenarios are then presented, to demonstrate the validity of the approach. © 2005 IEEE computer Society. All rights reserved.

关键词： Stereo vision

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