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 m...
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.
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-ampl...
详细信息
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 electrogast...
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-basedrepresentations 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.
this book constitutes the refereed proceedings of the 9th IAPR-TC-15 internationalworkshop on graph-basedrepresentations in patternrecognition, GbRPR 2013, held in Vienna, Austria, in May 2013. the 24 papers presen...
ISBN:
(数字)9783642382215
ISBN:
(纸本)9783642382208;9783642382215
this book constitutes the refereed proceedings of the 9th IAPR-TC-15 internationalworkshop on graph-basedrepresentations in patternrecognition, 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; graphrepresentations, segmentation and shape; and search in graphs.
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 de...
详细信息
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.
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 ba...
详细信息
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 (withthe 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.
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 ...
详细信息
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 internationalworkshop 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.
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 ...
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 patternrecognition;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.
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 ...
详细信息
暂无评论