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检索条件"任意字段=3rd IAPR Workshop on Artificial Neural Networks in Pattern Recognition"

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artificial neural networks in pattern recognition: 6th iapr TC 3 International workshop, ANNPR 2014, Montreal, QC, Canada, October 6-8, 2014. Proceedings 1

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丛书名： Lecture Notes in Computer Science 8774 Lecture Notes in artificial Intelligence

2014年

作者： Neamat El Gayar, Friedhelm Schwenker, Cheng Suen (eds.)

ISBN: (数字)9783319116563

ISBN: (纸本)9783319116556;9783319116563

This book constitutes the refereed proceedings of the 6th iapr TC3 International workshop on artificial neural networks in pattern recognition, ANNPR 2014, held in Montreal, QC, Canada, in October 2014. The 24 revised full papers presented were carefully reviewed and selected from 37 submissions for inclusion in this volume. They cover a large range of topics in the field of learning algorithms and architectures and discussing the latest research, results, and ideas in these areas.

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artificial neural networks in pattern recognition - 5th INNS iapr TC 3 GIRPR workshop, ANNPR 2012, Proceedings

Artificial Neural Networks in Pattern Recognition - 5th INNS...

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5th INNS iapr TC 3 GIRPR workshop on artificial neural networks for pattern recognition, ANNPR 2012

ISBN: (纸本)9783642332111

The proceedings contain 21 papers. The topics discussed include: how to quantitatively compare data dissimilarities for unsupervised machine learning?;kernel robust soft learning vector quantization;incremental learning by message passing in hierarchical temporal memory;representative prototype sets for data characterization and classification;feature selection by block addition and block deletion;feature selection by block addition and block deletion;towards a novel probabilistic graphical model of sequential data: fundamental notions and a solution to the problem of parameter learning;towards a novel probabilistic graphical model of sequential data: a solution to the problem of structure learning and an empirical evaluation;statistical recognition of a set of patterns using novel probability neural network;and on graph-associated matrices and their eigenvalues for optical character recognition.

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artificial neural networks in pattern recognition - 4th iapr TC3 workshop, ANNPR 2010, Proceedings

Artificial Neural Networks in Pattern Recognition - 4th IAPR...

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4th iapr TC3 workshop on artificial neural networks in pattern recognition, ANNPR 2010

ISBN: (纸本)3642121586

The proceedings contain 24 papers. The topics discussed include: pattern classification using a penalized likelihood method;evaluation of feature selection by multiclass kernel discriminant analysis;correlation-based and causal feature selection analysis for ensemble classifiers;a new Monte Carlo-based error rate estimator;recognition of sequences of graphical patterns;maximum echo-state-likelihood networks for emotion recognition;robustness analysis of eleven linear classifiers in extremely high-dimensional feature spaces;global coordination based on matrix neural gas for dynamic texture synthesis;sic-means: a semi-fuzzy approach for clustering data streams using C-means;the mathematics of divergence based online learning in vector quantization;cluster analysis of cortical pyramidal neurons using SOM;neural network cascade for facial feature localization;and a hidden Markov model based approach for facial expression recognition in image sequences.

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10th iapr TC3 International workshop on artificial neural networks in pattern recognition, ANNPR 2022

10th IAPR TC3 International Workshop on Artificial Neural Ne...

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10th iapr TC3 International workshop on artificial neural networks in pattern recognition, ANNPR 2022

ISBN: (纸本)9783031206498

The proceedings contain 16 papers. The special focus in this conference is on artificial neural networks in pattern recognition. The topics include: Sequence-to-Sequence CNN-BiLSTM Based Glottal Closure Instant Detection from Raw Speech;preface;graph Augmentation for neural networks Using Matching-Graphs;Mono vs Multilingual BERT for Hate Speech Detection and Text Classification: A Case Study in Marathi;transformer-Encoder Generated Context-Aware Embeddings for Spell Correction;assessment of Pharmaceutical Patent Novelty with Siamese neural networks;white Blood Cell Classification of Porcine Blood Smear Images;medical Deepfake Detection using 3-Dimensional neural Learning;a Study on the Autonomous Detection of Impact Craters;utilization of Vision Transformer for Classification and Ranking of Video Distortions;a Novel Representation of Graphical patterns for Graph Convolution networks;minimizing Cross Intersections in Graph Drawing via Linear Splines;multi-stage Bias Mitigation for Individual Fairness in Algorithmic Decisions;do Minimal Complexity Least Squares Support Vector Machines Work?.

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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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6th iapr TC3 International workshop on artificial neural networks for pattern recognition, ANNPR 2014

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6th iapr TC3 International workshop on artificial neural networks for pattern recognition, ANNPR 2014

ISBN: (纸本)9783319116556

The proceedings contain 27 papers. The special focus in this conference is on artificial neural networks for pattern recognition. The topics include: Large margin distribution learning;a decorrelation approach for pruning of multilayer perceptron networks;unsupervised active learning of CRF model for cross-lingual named entity recognition;incremental feature selection by block addition and block deletion using least squares SVRs;low-dimensional data representation in data analysis;analyzing dynamic ensemble selection techniques using dissimilarity analysis;hidden Markov models based on generalized Dirichlet mixtures for proportional data modeling;majority-class aware support vector domain oversampling for imbalanced classification problems;forward and backward forecasting ensembles for the estimation of time series missing data;dynamic weighted fusion of adaptive classifier ensembles based on changing data streams;combining bipartite graph matching and beam search for graph edit distance approximation;computing upper and lower bounds of graph edit distance in cubic time;a new multi-class fuzzy support vector machine algorithm;a reinforcement learning algorithm to train a Tetris playing agent;automatic bridge crack detection - a texture analysis-based approach;part-based high accuracy recognition of serial numbers in bank notes;comparative study of feature selection for white blood cell differential counts in low resolution images;end-shape recognition for Arabic handwritten text segmentation;intelligent ensemble systems for modeling NASDAQ microstructure;face recognition based on discriminative dictionary with multilevel feature fusion;investigating of preprocessing techniques and novel features in recognition of handwritten Arabic characters and a time series classification approach for motion analysis using ensembles in ubiquitous healthcare systems.

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8th iapr TC3 workshop on artificial neural networks for pattern recognition, ANNPR 2018

8th IAPR TC3 workshop on Artificial Neural Networks for Patt...

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8th iapr TC3 workshop on artificial neural networks for pattern recognition, ANNPR 2018

ISBN: (纸本)9783319999777

The proceedings contain 31 papers. The special focus in this conference is on artificial neural networks for pattern recognition. The topics include: A κ-nearest neighbor based algorithm for multi-instance multi-label active learning;manifold learning regression with non-stationary kernels;f-Measure Curves for Visualizing Classifier Performance with Imbalanced Data;maximum-likelihood estimation of neural mixture densities: model, algorithm, and preliminary experimental evaluation;generating Bounding Box Supervision for Semantic Segmentation with Deep Learning;inductive–transductive learning with graph neural networks;bounded rational decision-making with adaptive neural network priors;feature selection with rényi min-entropy;extracting gamma-ray information from images with convolutional neural network methods on simulated cherenkov telescope array data;deep learning in the wild;automatic hand sign recognition: Identify unusuality through latent cognizance;cascade of ordinal classification and local regression for audio-based affect estimation;combining classical and deep learning methods for twitter sentiment analysis;PHoG features and kullback-leibler divergence based ranking method for handwriting recognition;pattern recognition pipeline for neuroimaging data;anomaly pattern recognition with privileged information for sensor fault detection;Capturing suprasegmental features of a voice with RNNs for improved speaker clustering;Trace and detect adversarial attacks on CNNs using feature response maps;Video and audio data extraction for retrieval, ranking and recapitulation (VADER3);ATM protection using embedded deep learning solutions;effect of equality constraints to unconstrained large margin distribution machines;object detection in floor plan images;historical handwritten document segmentation by using a weighted loss;DLL: A fast deep neural network library;selecting features from foreign classes.

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9th iapr TC3 International workshop on artificial neural networks in pattern recognition, ANNPR 2020

9th IAPR TC3 International Workshop on Artificial Neural Net...

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9th iapr TC3 International workshop on artificial neural networks in pattern recognition, ANNPR 2020

ISBN: (纸本)9783030583088

The proceedings contain 24 papers. The special focus in this conference is on artificial neural networks in pattern recognition. The topics include: Named entity disambiguation at scale;geometric attention for prediction of differential properties in 3d point clouds;preface;deep learning methods for image guidance in radiation therapy;how (not) to measure bias in face recognition networks;feature extraction: A time window analysis based on the x-ite pain database;pain intensity recognition - an analysis of short-time sequences in a real-world scenario;a deep learning approach for efficient registration of dual view mammography;deep transfer learning for texture classification in colorectal cancer histology;applications of generative adversarial networks to dermatologic imaging;typing plasmids with distributed sequence representation;kp-yolo: A modification of yolo algorithm for the keypoint-based detection of qr codes;using mask r-cnn for image-based wear classification of solid carbide milling and drilling tools;a hybrid deep learning approach for forecasting air temperature;intentional image similarity search;using cnns to optimize numerical simulations in geotechnical engineering;going for 2d or 3d? investigating various machine learning approaches for peach variety identification;a transfer learning end-to-end arabic text-to-speech (tts) deep architecture;ml-based trading models: An investigation during covid-19 pandemic crisis;innvestigate-gui - explaining neural networks through an interactive visualization tool;structured (de)composable representations trained with neural networks;long distance relationships without time travel: Boosting the performance of a sparse predictive autoencoder in sequence modeling.

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11th iapr TC3 workshop on artificial neural networks in pattern recognition, ANNPR 2024

11th IAPR TC3 workshop on Artificial Neural Networks in Patt...

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11th iapr TC3 workshop on artificial neural networks in pattern recognition, ANNPR 2024

ISBN: (纸本)9783031716010

The proceedings contain 27 papers. The special focus in this conference is on artificial neural networks in pattern recognition. The topics include: neural Decompiling of Tracr Transformers;pitfalls in Processing Infinite-Length Sequences with Popular Approaches for Sequential Data;robust Clustering with McDonald’s Beta-Liouville Mixture Models for Proportional Data;evaluating Support Vector Machines with Multiple Kernels by Random Search;Automatic Interpretation of 18F-Fluorocholine PET/CT Findings in Patients with Primary Hyperparathyroidism: A Novel Dataset with Benchmarks;a Hybrid Neuroevolutionary Approach to the Design of Convolutional neural networks for 2D and 3D Medical Image Segmentation;An Improved Pix2Pix GAN for Medical Image Generation;vision Transformer Features-Based Leukemia Classification;comparative Study of Deep Learning Models in Melanoma Detection;a Metaheuristic Optimization Based Deep Feature Selection for Oral Cancer Classification;machine Learning for Clinical Score Prediction from Longitudinal Dataset: A Case Study on Parkinson’s Disease;explaining Network Decision Provides Insights on the Causal Interaction Between Brain Regions in a Motor Imagery Task;Multi-modal Decoding of Reach-to-Grasping from EEG and EMG via neural networks;VAeViT: Fusing Multi-views for Complete 3D Object recognition;leveraging Transformers for Weakly Supervised Object Localization in Unconstrained Videos;palmprint Classification via Filter Faces and Feature Extraction;deep Multi-label Classification of Personality with Handwriting Analysis;license Plate Detection and Character recognition Using Deep Learning and Font Evaluation;experiments in Modeling Disagreement;deep Multiresolution Wavelet Transform for Speech Emotion Assessment of High-Risk Suicide Callers;Dynamic HumTrans: Humming Transcription Using CNNs and Dynamic Programming;Leveraging LSTM Embeddings for River Water Temperature Modeling;research on the Identification of Common Economic Shellfish in Jiang

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Real-time emotion recognition from speech using echo state networks

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3rd iapr workshop on artificial neural networks in pattern recognition

作者： Scherer, Stefan Oubbati, Mohamed Schwenker, Friedhelm Palm, Guenther Univ Ulm Inst Neural Informat Proc D-89069 Ulm Germany

ISBN: (纸本)9783540699385

The goal of this work is to investigate real-time emotion recognition in noisy environments. Our approach is to solve this problem using novel recurrent neural networks called echo state networks (ESN). ESNs utilizing the sequential characteristics of biologically motivated modulation spectrum features are easy to train and robust towards noisy real world conditions. The standard Berlin Database of Emotional Speech is used to evaluate the performance of the proposed approach. The experiments reveal promising results overcoming known difficulties and drawbacks of common approaches.

关键词： Recurrent neural networks

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