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

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PRNI 2016 - 6th international workshop on pattern recognition in Neuroimaging

PRNI 2016 - 6th International Workshop on Pattern Recognitio...

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6th international workshop on pattern recognition in Neuroimaging, PRNI 2016

ISBN: (纸本)9781467365307

the proceedings contain 34 papers. the topics discussed include: fixed low-rank EEG spatial filter estimation for emotion recognition induced by movies;recovery of non-linear cause-effect relationships from linearly mixed neuroimaging data;collapsed variational Bayesian inference of the author-topic model: application to large-scale coordinate-based meta-analysis;voxel importance in classifier ensembles based on sign consistency patterns: application to sMRI;novel histogram-weighted cortical thickness networks and a multi-scale analysis of predictive;classification-based tests for neuroimaging data analysis: comparison of best practices;M/EEG source localization with multi-scale time-frequency dictionaries;and towards tailoring non-invasive brain stimulation using real-time fMRI and Bayesian optimization.

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Synergism of spectral and coupling modalities in epileptic focus localization from iEEG recordings 6

Synergism of spectral and coupling modalities in epileptic f...

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6th international workshop on pattern recognition in Neuroimaging, PRNI 2016

作者： Nánási, Tibor File, Bálint Tóth, Emília Entz, László Ulbert, István Fabó, Dániel ErÅ'Ss, Lóránd Insitute of Cognitive Neuroscience and Psychology Research Centre for Natural Sciences Hungarian Academy of Sciences Budapest Hungary Faculty of Information Technology and Bionics Pázmány Péter Catholic University Budapest Hungary Department of Functional Neurosurgery Center of Neuromodulation National Institute of Clinical Neurosciences Budapest Hungary Epilepsy Centrum Deptartment of Neurology National Institute of Clinical Neurosciences Budapest Hungary

ISBN: (纸本)9781467365307

determining the epileptogenic zone (EZ) from intracranial electroencephalography (iEEG) recordings is an important but nontrivial task. In this pilot study we demonstrate the usefulness of phasesynchronized phase-amplitude coupling constellations as a hybrid construct from well-established phase-amplitude and phase-phase coupling measurements. Also, we introduce a heuristic measure related to spectral entropy which can further improve the specificity of EZ detection. Our analysis works on seizure-free sleep iEEG grid data abundant in a typical clinical setting and aside from the initial frequency band definitions operates in a thresholdfree data-driven manner. © 2016 IEEE.

关键词： graph theory

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7th IAPR TC3 workshop on Artificial Neural Networks in pattern recognition, ANNPR 2016

7th IAPR TC3 Workshop on Artificial Neural Networks in Patte...

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7th IAPR TC3 workshop on Artificial Neural Networks in pattern recognition, ANNPR 2016

ISBN: (纸本)9783319461816

the proceedings contain 27 papers. the special focus in this conference is on Learning Algorithms, Architectures and Applications. the topics include: A spiking neural network for personalised modelling of electrogastrography;improving generalization abilities of maximal average margin classifiers;finding small sets of random Fourier features for shift-invariant kernel approximation;incremental construction of low-dimensional data representations;soft-constrained nonparametric density estimation with artificial neural networks;interpretable classifiers in precision medicine;on the evaluation of tensor-based representations for optimum-path forest classification;on the harmony search using quaternions;learning parameters in deep belief networks through firefly algorithm;towards effective classification of imbalanced data with convolutional neural networks;on CPU performance optimization of restricted Boltzmann machine and convolutional RBM;comparing incremental learning strategies for convolutional neural networks;approximation of graph edit distance by means of a utility matrix;time series classification in reservoir- and model-space;objectness scoring and detection proposals in forward-looking sonar images with convolutional neural networks;background categorization for automatic animal detection in aerial videos using neural networks;predictive segmentation using multichannel neural networks in Arabic OCR system;quad-tree based image segmentation and feature extraction to recognize online handwritten bangla characters;using radial basis function neural networks for continuous and discrete pain estimation from bio-physiological signals;emotion recognition in speech with deep learning architectures and on gestures and postural behavior as a modality in ensemble methods.

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graph-based representations in pattern recognition: 9th IAPR-TC-15 international workshop, GbRPR 2013, Vienna, Austria, May 15-17, 2013. Proceedings 1

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丛书名： Lecture Notes in Computer Science 7877 Image Processing, Computer Vision, pattern recognition, and graphics

2013年

作者： Mario Vento (auth.), Walter G. Kropatsch, Nicole M. Artner, Yll Haxhimusa, Xiaoyi Jiang (eds.)

ISBN: (数字)9783642382215

ISBN: (纸本)9783642382208;9783642382215

this book constitutes the refereed proceedings of the 9th IAPR-TC-15 international workshop on graph-based representations in pattern recognition, GbRPR 2013, held in Vienna, Austria, in May 2013. the 24 papers presented in this volume were carefully reviewed and selected from 27 submissions. they are organized in topical sections named: finding subregions in graphs; graph matching; classification; graph kernels; properties of graphs; topology; graph representations, segmentation and shape; and search in graphs.

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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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Persistence based on LBP Scale Space 6th

Persistence Based on LBP Scale Space

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6th international workshop on Computational Topology in Image Context (CTIC)

作者： Janusch, Ines Kropatsch, Walter G. TU Wien Inst Comp Graph & Algorithms Pattern Recognit & Image Proc Grp Vienna Austria

ISBN: (纸本)9783319394404;9783319394411

this paper discusses the connection between the texture operator LBP (local binary pattern) and an application of LBPs to persistent homology. A shape representation - the LBP scale space is defined as a filtration based on the variation of an LBP parameter. A relation between the LBP scale space and a variation of thresholds used in the segmentation of a graylevel image is discussed. Using the LBP scale space a characterization of (parts of) shapes is demonstrated based on simple shape primitives, the observations may also be generalized for smooth curves. the LBP scale space is augmented by associating it with polar coordinates (with the origin located at the LBP center). In this way a procedure of shape reconstruction based on the LBP scale space is defined and its reconstruction accuracy is demonstrated in an experiment. Furthermore, this augmented LBP scale space representation is invariant to translation and rotation of the shape.

关键词： LBP Persistence Scale space Filtration Shape analysis Shape reconstruction Segmentation

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14th European Conference on Computer Vision, ECCV 2016

14th European Conference on Computer Vision, ECCV 2016

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Computer Vision - ECCV 2016 workshops, Proceedings

ISBN: (纸本)9783319494081

the proceedings contain 75 papers. the special focus in this conference is on W04 - Brave New Ideas For Motion representations, W06 - Geometry Meets Deep Learning, W14 - Recovering 6D Object Pose and W20 - the Second international workshop on Video Segmentation. the topics include: Unsupervised learning of optical flow via brightness constancy and motion smoothness;human action recognition without human;motion representation with acceleration images;segmentation free object discovery in video;human pose estimation in space and time using 3D CNN;to infer the property of a dynamic object based on its motion pattern;temporal convolutional networks;making a case for learning motion representations with phase;neural network library for geometric computer vision;learning covariant feature detectors;scene segmentation driven by deep learning and surface fitting;a CNN cascade for landmark guided semantic part segmentation;overcoming occlusion with inverse graphics;deep kinematic pose regression;learning the structure of objects from web supervision;deep volumetric shape learning without object labels;deep shape from a low number of silhouettes;deep disentangled representations for volumetric reconstruction;monocular surface reconstruction using 3d deformable part models;deep bimodal regression for apparent personality analysis;RGB-depth database for human head pose estimation;audiovisual deep residual networks for multimodal apparent personality trait recognition;deep learning for facial action unit detection under large head poses;first round challenge on first impressions - dataset and results and best practices for fine-tuning visual classifiers to new domains.

关键词： Computer vision

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graph-based representations in pattern recognition - 9th IAPR-TC-15 international workshop, GbRPR 2013, Proceedings

Graph-Based Representations in Pattern Recognition - 9th IAP...

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9th IAPR-TC-15 international workshop on graph-based representations in pattern recognition, GbRPR 2013

ISBN: (纸本)9783642382208

the proceedings contain 26 papers. the topics discussed include: a one hour trip in the world of graphs, looking at the papers of the last ten years;a unified framework for strengthening topological node features and its application to subgraph isomorphism detection;on the complexity of submap isomorphism;flooding edge weighted graphs;graph matching with nonnegative sparse model;active-learning query strategies applied to select a graph node given a graph labeling;a comparison of explicit and implicit graph embedding methods for pattern recognition;adjunctions on the lattice of dendrograms;a continuous-time quantum walk kernel for unattributed graphs;relevant cycle hypergraph representation for molecules;a quantum Jensen-Shannon graph kernel using the continuous-time quantum walk;and a novel software toolkit for graph edit distance computation.

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graph-based representations in pattern recognition: 9th IAPR-TC-15 international workshop, GbRPR 2013, Vienna, Austria, May 15-17, 2013, Proceedings

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2013年

作者： Walter G Kropatsch Nicole M Artner Yll Haxhimusa

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Reeb graphs through local binary patterns 10

Reeb graphs through local binary patterns

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10th IAPR-TC-15 international workshop on graph-based representations in pattern recognition, GbRPR 2015

作者： Janusch, Ines Kropatsch, Walter G. Pattern Recognition and Image Processing Group Institute of Computer Graphics and Algorithms Vienna University of Technology Vienna Austria

ISBN: (纸本)9783319182230

this paper presents an approach to derive critical points of a shape, the basis of a Reeb graph, using a combination of a medial axis skeleton and features along this skeleton. A Reeb graph captures the topology of a shape. the nodes in the graph represent critical points (positions of change in the topology), while edges represent topological persistence. We present an approach to compute such critical points using Local Binary patterns. For one pixel the Local Binary pattern feature vector is derived comparing this pixel to its neighbouring pixels in an environment of a certain radius. We start with an initial segmentation and a medial axis representation. Along this axis critical points are computed using Local Binary patterns with the radius, defining the neighbouring pixels, set a bit larger than the radius according to the medial axis transformation. Critical points obtained in this way form the node set in a Reeb graph, edges are given through the connectivity of the skeleton. this approach aims at improving the representation of flawed segmented data. In the same way segmentation artefacts, as for example single pixels representing noise, may be corrected based on this analysis. © Springer international Publishing Switzerland 2015.

关键词： Image segmentation

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