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Auteur Věra Kůrková-Pohlova |
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Artificial Neural Networks and Machine Learning – ICANN 2018 / Věra Kůrková-Pohlova ; SpringerLink (Online service) ; Yannis Manolopoulos ; Barbara Hammer ; Lazaros S. Iliadis ; Ilias Maglogiannis / Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer (2018)
Titre : Artificial Neural Networks and Machine Learning – ICANN 2018 : 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part I Type de document : document électronique Auteurs : Věra Kůrková-Pohlova, ; SpringerLink (Online service) ; Yannis Manolopoulos, ; Barbara Hammer, ; Lazaros S. Iliadis , ; Ilias Maglogiannis, Editeur : Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer Année de publication : 2018 Collection : Lecture Notes in Computer Science - LNCS, ISSN 0302-9743 num. 11139 Importance : XLIII, 824 p. 311 illus Présentation : online resource ISBN/ISSN/EAN : 978-3-030-01418-6 Langues : Anglais (eng) Tags : Artificial intelligence Computer vision Computer network architectures Information systems Computer security Computer software Artificial Intelligence Image Processing and Computer Vision Computer Systems Organization and Communication Networks Information Systems and Communication Service Systems and Data Security Algorithm Analysis and Problem Complexity Résumé : This three-volume set LNCS 11139-11141 constitutes the refereed proceedings of the 27th International Conference on Artificial Neural Networks, ICANN 2018, held in Rhodes, Greece, in October 2018. The papers presented in these volumes was carefully reviewed and selected from total of 360 submissions. They are related to the following thematic topics: AI and Bioinformatics, Bayesian and Echo State Networks, Brain Inspired Computing, Chaotic Complex Models, Clustering, Mining, Exploratory Analysis, Coding Architectures, Complex Firing Patterns, Convolutional Neural Networks, Deep Learning (DL), DL in Real Time Systems, DL and Big Data Analytics, DL and Big Data, DL and Forensics, DL and Cybersecurity, DL and Social Networks, Evolving Systems – Optimization, Extreme Learning Machines, From Neurons to Neuromorphism, From Sensation to Perception, From Single Neurons to Networks, Fuzzy Modeling, Hierarchical ANN, Inference and Recognition, Information and Optimization, Interacting with The Brain, Machine Learning (ML), ML for Bio Medical systems, ML and Video-Image Processing, ML and Forensics, ML and Cybersecurity, ML and Social Media, ML in Engineering, Movement and Motion Detection, Multilayer Perceptrons and Kernel Networks, Natural Language, Object and Face Recognition, Recurrent Neural Networks and Reservoir Computing, Reinforcement Learning, Reservoir Computing, Self-Organizing Maps, Spiking Dynamics/Spiking ANN, Support Vector Machines, Swarm Intelligence and Decision-Making, Text Mining, Theoretical Neural Computation, Time Series and Forecasting, Training and Learning Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=142932 Artificial Neural Networks and Machine Learning – ICANN 2018 : 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part I [document électronique] / Věra Kůrková-Pohlova, ; SpringerLink (Online service) ; Yannis Manolopoulos, ; Barbara Hammer, ; Lazaros S. Iliadis , ; Ilias Maglogiannis, . - Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer, 2018 . - XLIII, 824 p. 311 illus : online resource. - (Lecture Notes in Computer Science - LNCS, ISSN 0302-9743; 11139) .
ISBN : 978-3-030-01418-6
Langues : Anglais (eng)
Tags : Artificial intelligence Computer vision Computer network architectures Information systems Computer security Computer software Artificial Intelligence Image Processing and Computer Vision Computer Systems Organization and Communication Networks Information Systems and Communication Service Systems and Data Security Algorithm Analysis and Problem Complexity Résumé : This three-volume set LNCS 11139-11141 constitutes the refereed proceedings of the 27th International Conference on Artificial Neural Networks, ICANN 2018, held in Rhodes, Greece, in October 2018. The papers presented in these volumes was carefully reviewed and selected from total of 360 submissions. They are related to the following thematic topics: AI and Bioinformatics, Bayesian and Echo State Networks, Brain Inspired Computing, Chaotic Complex Models, Clustering, Mining, Exploratory Analysis, Coding Architectures, Complex Firing Patterns, Convolutional Neural Networks, Deep Learning (DL), DL in Real Time Systems, DL and Big Data Analytics, DL and Big Data, DL and Forensics, DL and Cybersecurity, DL and Social Networks, Evolving Systems – Optimization, Extreme Learning Machines, From Neurons to Neuromorphism, From Sensation to Perception, From Single Neurons to Networks, Fuzzy Modeling, Hierarchical ANN, Inference and Recognition, Information and Optimization, Interacting with The Brain, Machine Learning (ML), ML for Bio Medical systems, ML and Video-Image Processing, ML and Forensics, ML and Cybersecurity, ML and Social Media, ML in Engineering, Movement and Motion Detection, Multilayer Perceptrons and Kernel Networks, Natural Language, Object and Face Recognition, Recurrent Neural Networks and Reservoir Computing, Reinforcement Learning, Reservoir Computing, Self-Organizing Maps, Spiking Dynamics/Spiking ANN, Support Vector Machines, Swarm Intelligence and Decision-Making, Text Mining, Theoretical Neural Computation, Time Series and Forecasting, Training and Learning Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=142932 Artificial Neural Networks and Machine Learning – ICANN 2018 / Věra Kůrková-Pohlova ; SpringerLink (Online service) ; Yannis Manolopoulos ; Barbara Hammer ; Lazaros S. Iliadis ; Ilias Maglogiannis / Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer (2018)
Titre : Artificial Neural Networks and Machine Learning – ICANN 2018 : 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part II Type de document : document électronique Auteurs : Věra Kůrková-Pohlova, ; SpringerLink (Online service) ; Yannis Manolopoulos, ; Barbara Hammer, ; Lazaros S. Iliadis , ; Ilias Maglogiannis, Editeur : Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer Année de publication : 2018 Collection : Lecture Notes in Computer Science - LNCS, ISSN 0302-9743 num. 11140 Importance : XXVIII, 632 p. 242 illus Présentation : online resource ISBN/ISSN/EAN : 978-3-030-01421-6 Langues : Anglais (eng) Tags : Artificial intelligence Computer vision Computer network architectures Information systems Computer security Computer software Artificial Intelligence Image Processing and Computer Vision Computer Systems Organization and Communication Networks Information Systems and Communication Service Systems and Data Security Algorithm Analysis and Problem Complexity Résumé : This three-volume set LNCS 11139-11141 constitutes the refereed proceedings of the 27th International Conference on Artificial Neural Networks, ICANN 2018, held in Rhodes, Greece, in October 2018. The 139 full and 28 short papers as well as 41 full poster papers and 41 short poster papers presented in these volumes was carefully reviewed and selected from total of 360 submissions. They are related to the following thematic topics: AI and Bioinformatics, Bayesian and Echo State Networks, Brain Inspired Computing, Chaotic Complex Models, Clustering, Mining, Exploratory Analysis, Coding Architectures, Complex Firing Patterns, Convolutional Neural Networks, Deep Learning (DL), DL in Real Time Systems, DL and Big Data Analytics, DL and Big Data, DL and Forensics, DL and Cybersecurity, DL and Social Networks, Evolving Systems – Optimization, Extreme Learning Machines, From Neurons to Neuromorphism, From Sensation to Perception, From Single Neurons to Networks, Fuzzy Modeling, Hierarchical ANN, Inference and Recognition, Information and Optimization, Interacting with The Brain, Machine Learning (ML), ML for Bio Medical systems, ML and Video-Image Processing, ML and Forensics, ML and Cybersecurity, ML and Social Media, ML in Engineering, Movement and Motion Detection, Multilayer Perceptrons and Kernel Networks, Natural Language, Object and Face Recognition, Recurrent Neural Networks and Reservoir Computing, Reinforcement Learning, Reservoir Computing, Self-Organizing Maps, Spiking Dynamics/Spiking ANN, Support Vector Machines, Swarm Intelligence and Decision-Making, Text Mining, Theoretical Neural Computation, Time Series and Forecasting, Training and Learning Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=142928 Artificial Neural Networks and Machine Learning – ICANN 2018 : 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part II [document électronique] / Věra Kůrková-Pohlova, ; SpringerLink (Online service) ; Yannis Manolopoulos, ; Barbara Hammer, ; Lazaros S. Iliadis , ; Ilias Maglogiannis, . - Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer, 2018 . - XXVIII, 632 p. 242 illus : online resource. - (Lecture Notes in Computer Science - LNCS, ISSN 0302-9743; 11140) .
ISBN : 978-3-030-01421-6
Langues : Anglais (eng)
Tags : Artificial intelligence Computer vision Computer network architectures Information systems Computer security Computer software Artificial Intelligence Image Processing and Computer Vision Computer Systems Organization and Communication Networks Information Systems and Communication Service Systems and Data Security Algorithm Analysis and Problem Complexity Résumé : This three-volume set LNCS 11139-11141 constitutes the refereed proceedings of the 27th International Conference on Artificial Neural Networks, ICANN 2018, held in Rhodes, Greece, in October 2018. The 139 full and 28 short papers as well as 41 full poster papers and 41 short poster papers presented in these volumes was carefully reviewed and selected from total of 360 submissions. They are related to the following thematic topics: AI and Bioinformatics, Bayesian and Echo State Networks, Brain Inspired Computing, Chaotic Complex Models, Clustering, Mining, Exploratory Analysis, Coding Architectures, Complex Firing Patterns, Convolutional Neural Networks, Deep Learning (DL), DL in Real Time Systems, DL and Big Data Analytics, DL and Big Data, DL and Forensics, DL and Cybersecurity, DL and Social Networks, Evolving Systems – Optimization, Extreme Learning Machines, From Neurons to Neuromorphism, From Sensation to Perception, From Single Neurons to Networks, Fuzzy Modeling, Hierarchical ANN, Inference and Recognition, Information and Optimization, Interacting with The Brain, Machine Learning (ML), ML for Bio Medical systems, ML and Video-Image Processing, ML and Forensics, ML and Cybersecurity, ML and Social Media, ML in Engineering, Movement and Motion Detection, Multilayer Perceptrons and Kernel Networks, Natural Language, Object and Face Recognition, Recurrent Neural Networks and Reservoir Computing, Reinforcement Learning, Reservoir Computing, Self-Organizing Maps, Spiking Dynamics/Spiking ANN, Support Vector Machines, Swarm Intelligence and Decision-Making, Text Mining, Theoretical Neural Computation, Time Series and Forecasting, Training and Learning Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=142928 Artificial Neural Networks and Machine Learning – ICANN 2018 / Věra Kůrková-Pohlova ; SpringerLink (Online service) ; Yannis Manolopoulos ; Barbara Hammer ; Lazaros S. Iliadis ; Ilias Maglogiannis / Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer (2018)
Titre : Artificial Neural Networks and Machine Learning – ICANN 2018 : 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part III Type de document : document électronique Auteurs : Věra Kůrková-Pohlova, ; SpringerLink (Online service) ; Yannis Manolopoulos, ; Barbara Hammer, ; Lazaros S. Iliadis , ; Ilias Maglogiannis, Editeur : Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer Année de publication : 2018 Collection : Lecture Notes in Computer Science - LNCS, ISSN 0302-9743 num. 11141 Importance : XXIX, 846 p. 311 illus Présentation : online resource ISBN/ISSN/EAN : 978-3-030-01424-7 Langues : Anglais (eng) Tags : Artificial intelligence Computer vision Computer network architectures Information systems Computer security Computer software Artificial Intelligence Image Processing and Computer Vision Computer Systems Organization and Communication Networks Information Systems and Communication Service Systems and Data Security Algorithm Analysis and Problem Complexity Résumé : This three-volume set LNCS 11139-11141 constitutes the refereed proceedings of the 27th International Conference on Artificial Neural Networks, ICANN 2018, held in Rhodes, Greece, in October 2018. The papers presented in these volumes was carefully reviewed and selected from total of 360 submissions. They are related to the following thematic topics: AI and Bioinformatics, Bayesian and Echo State Networks, Brain Inspired Computing, Chaotic Complex Models, Clustering, Mining, Exploratory Analysis, Coding Architectures, Complex Firing Patterns, Convolutional Neural Networks, Deep Learning (DL), DL in Real Time Systems, DL and Big Data Analytics, DL and Big Data, DL and Forensics, DL and Cybersecurity, DL and Social Networks, Evolving Systems – Optimization, Extreme Learning Machines, From Neurons to Neuromorphism, From Sensation to Perception, From Single Neurons to Networks, Fuzzy Modeling, Hierarchical ANN, Inference and Recognition, Information and Optimization, Interacting with The Brain, Machine Learning (ML), ML for Bio Medical systems, ML and Video-Image Processing, ML and Forensics, ML and Cybersecurity, ML and Social Media, ML in Engineering, Movement and Motion Detection, Multilayer Perceptrons and Kernel Networks, Natural Language, Object and Face Recognition, Recurrent Neural Networks and Reservoir Computing, Reinforcement Learning, Reservoir Computing, Self-Organizing Maps, Spiking Dynamics/Spiking ANN, Support Vector Machines, Swarm Intelligence and Decision-Making, Text Mining, Theoretical Neural Computation, Time Series and Forecasting, Training and Learning Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=142939 Artificial Neural Networks and Machine Learning – ICANN 2018 : 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part III [document électronique] / Věra Kůrková-Pohlova, ; SpringerLink (Online service) ; Yannis Manolopoulos, ; Barbara Hammer, ; Lazaros S. Iliadis , ; Ilias Maglogiannis, . - Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer, 2018 . - XXIX, 846 p. 311 illus : online resource. - (Lecture Notes in Computer Science - LNCS, ISSN 0302-9743; 11141) .
ISBN : 978-3-030-01424-7
Langues : Anglais (eng)
Tags : Artificial intelligence Computer vision Computer network architectures Information systems Computer security Computer software Artificial Intelligence Image Processing and Computer Vision Computer Systems Organization and Communication Networks Information Systems and Communication Service Systems and Data Security Algorithm Analysis and Problem Complexity Résumé : This three-volume set LNCS 11139-11141 constitutes the refereed proceedings of the 27th International Conference on Artificial Neural Networks, ICANN 2018, held in Rhodes, Greece, in October 2018. The papers presented in these volumes was carefully reviewed and selected from total of 360 submissions. They are related to the following thematic topics: AI and Bioinformatics, Bayesian and Echo State Networks, Brain Inspired Computing, Chaotic Complex Models, Clustering, Mining, Exploratory Analysis, Coding Architectures, Complex Firing Patterns, Convolutional Neural Networks, Deep Learning (DL), DL in Real Time Systems, DL and Big Data Analytics, DL and Big Data, DL and Forensics, DL and Cybersecurity, DL and Social Networks, Evolving Systems – Optimization, Extreme Learning Machines, From Neurons to Neuromorphism, From Sensation to Perception, From Single Neurons to Networks, Fuzzy Modeling, Hierarchical ANN, Inference and Recognition, Information and Optimization, Interacting with The Brain, Machine Learning (ML), ML for Bio Medical systems, ML and Video-Image Processing, ML and Forensics, ML and Cybersecurity, ML and Social Media, ML in Engineering, Movement and Motion Detection, Multilayer Perceptrons and Kernel Networks, Natural Language, Object and Face Recognition, Recurrent Neural Networks and Reservoir Computing, Reinforcement Learning, Reservoir Computing, Self-Organizing Maps, Spiking Dynamics/Spiking ANN, Support Vector Machines, Swarm Intelligence and Decision-Making, Text Mining, Theoretical Neural Computation, Time Series and Forecasting, Training and Learning Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=142939 Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning / Igor V. Tetko ; SpringerLink (Online service) ; Věra Kůrková-Pohlova ; Pavel Karpov ; Fabian Theis / Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer (2019)
Titre : Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning : 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part II Type de document : document électronique Auteurs : Igor V. Tetko, ; SpringerLink (Online service) ; Věra Kůrková-Pohlova, ; Pavel Karpov, ; Fabian Theis, Editeur : Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer Année de publication : 2019 Collection : Lecture Notes in Computer Science - LNCS, ISSN 0302-9743 num. 11728 Importance : XXX, 807 p. 294 illus., 193 illus. in color Présentation : online resource ISBN/ISSN/EAN : 978-3-030-30484-3 Langues : Anglais (eng) Tags : Artificial intelligence Optical data processing Computer organization Computers Algorithms Computer security Artificial Intelligence Image Processing and Computer Vision Computer Systems Organization and Communication Networks Information Systems and Communication Service Algorithm Analysis and Problem Complexity Systems and Data Security Résumé : The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions. Note de contenu : Adaptive Graph Fusion for Unsupervised Feature Selection -- Unsupervised Feature Selection via Local Total-order Preservation -- Discrete Stochastic Search and its Application to Feature-Selection for Deep Relational Machines -- Joint Dictionary Learning for Unsupervised Feature Selection -- Comparison between Filter Criteria for Feature Selection in Regression -- CancelOut: A layer for feature selection in deep neural networks -- Adaptive-L2 Batch Neural Gas -- Application of Self Organizing Map to Preprocessing Input Vectors for Convolutional Neural Network -- Hierarchical Reinforcement Learning with Unlimited Recursive Subroutine Calls -- Automatic Augmentation by Hill Climbing -- Learning Camera-invariant Representation for Person Re-identification -- PA-RetinaNet: Path Augmented RetinaNet for Dense Object Detection -- Singular Value Decomposition and Neural Networks -- PCI: Principal Component Initialization for Deep Autoencoders -- Improving Weight Initialization of ReLU and Output Layers -- Post-synaptic potential regularization has potential -- A Novel Modification on the Levenberg-Marquardt Algorithm for Avoiding Overfitting in Neural Network Training -- Sign Based Derivative Filtering for Stochastic Gradient Descent -- Architecture-aware Bayesian Optimization for Neural Network Tuning -- Non-Convergence and Limit Cycles in the Adam Optimizer -- Learning Internal Dense But External Sparse Structures of Deep Convolutional Neural Network -- Using feature entropy to guide filter pruning for efficient convolutional networks -- Simultaneously Learning Architectures and Features of Deep Neural Networks -- Learning Sparse Hidden States in Long Short-Term Memory -- Multi-objective Pruning for CNNs using Genetic Algorithm -- Dynamically Sacrificing Accuracy for Reduced Computation: Cascaded Inference Based on Softmax Confidence -- Light-Weight Edge Enhanced Network for On-orbit Semantic Segmentation -- Local Normalization Based BN Layer Pruning -- On Practical Approach to Uniform Quantization of Non-redundant Neural Networks -- Residual learning for FC kernels of convolutional network -- A Novel Neural Network-based Symbolic Regression Method: Neuro-Encoded Expression Programming -- Compute-efficient neural network architecture optimization by a genetic algorithm -- Controlling Model Complexity in Probabilistic Model-Based Dynamic Optimization of Neural Network Structures -- Predictive Uncertainty Estimation with Temporal Convolutional Networks for Dynamic Evolutionary Optimization -- Sparse Recurrent Mixture Density Networks for Forecasting High Variability Time Series with Confidence Estimates -- A multitask learning neural network for short-term traffic speed prediction and confidence estimation -- Central-diffused Instance Generation Method in Class Incremental Learning -- Marginal Replay vs Conditional Replay for Continual Learning -- Simplified computation and interpretation of Fisher matrices in incremental learning with deep neural networks -- Active Learning for Image Recognition using a Visualization-Based User Interface -- Basic Evaluation Scenarios for Incrementally Trained Classifiers -- Embedding Complexity of Learned Representations in Neural Networks -- Joint Metric Learning on Riemannian Manifold of Global Gaussian Distributions -- Multi-Task Sparse Regression Metric Learning for Heterogeneous Classification -- Fast Approximate Geodesics for Deep Generative Models -- Spatial Attention Network for Few-Shot Learning -- Routine Modeling with Time Series Metric Learning -- Leveraging Domain Knowledge for Reinforcement Learning using MMC Architectures -- Conditions for Unnecessary Logical Constraints in Kernel Machines -- HiSeqGAN: Hierarchical Sequence Synthesis and Prediction -- DeepEX: Bridging the Gap Between Knowledge and Data Driven Techniques for Time Series Forecasting -- Transferable Adversarial Cycle Alignment for Domain Adaption -- Evaluation of domain adaptation approaches for robust classification of heterogeneous biological data sets -- Named Entity Recognition for Chinese Social Media with Domain Adversarial Training and Language Modeling -- Deep Domain Knowledge Distillation for Person Re-identification -- A study on catastrophic forgetting in deep LSTM networks -- A Label-specific Attention-based Network with Regularized Loss for Multi-label Classification -- An Empirical Study of Multi-domain and Multi-task Learning in Chinese Named Entity Recognition -- Filter Method Ensemble with Neural Networks -- Dynamic Centroid Insertion and Adjustment for Data Sets with Multiple Imbalanced Classes -- Increasing the Generalisaton Capacity of Conditional VAEs -- Playing the Large Margin Preference Game Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=148040 Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning : 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part II [document électronique] / Igor V. Tetko, ; SpringerLink (Online service) ; Věra Kůrková-Pohlova, ; Pavel Karpov, ; Fabian Theis, . - Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer, 2019 . - XXX, 807 p. 294 illus., 193 illus. in color : online resource. - (Lecture Notes in Computer Science - LNCS, ISSN 0302-9743; 11728) .
ISBN : 978-3-030-30484-3
Langues : Anglais (eng)
Tags : Artificial intelligence Optical data processing Computer organization Computers Algorithms Computer security Artificial Intelligence Image Processing and Computer Vision Computer Systems Organization and Communication Networks Information Systems and Communication Service Algorithm Analysis and Problem Complexity Systems and Data Security Résumé : The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions. Note de contenu : Adaptive Graph Fusion for Unsupervised Feature Selection -- Unsupervised Feature Selection via Local Total-order Preservation -- Discrete Stochastic Search and its Application to Feature-Selection for Deep Relational Machines -- Joint Dictionary Learning for Unsupervised Feature Selection -- Comparison between Filter Criteria for Feature Selection in Regression -- CancelOut: A layer for feature selection in deep neural networks -- Adaptive-L2 Batch Neural Gas -- Application of Self Organizing Map to Preprocessing Input Vectors for Convolutional Neural Network -- Hierarchical Reinforcement Learning with Unlimited Recursive Subroutine Calls -- Automatic Augmentation by Hill Climbing -- Learning Camera-invariant Representation for Person Re-identification -- PA-RetinaNet: Path Augmented RetinaNet for Dense Object Detection -- Singular Value Decomposition and Neural Networks -- PCI: Principal Component Initialization for Deep Autoencoders -- Improving Weight Initialization of ReLU and Output Layers -- Post-synaptic potential regularization has potential -- A Novel Modification on the Levenberg-Marquardt Algorithm for Avoiding Overfitting in Neural Network Training -- Sign Based Derivative Filtering for Stochastic Gradient Descent -- Architecture-aware Bayesian Optimization for Neural Network Tuning -- Non-Convergence and Limit Cycles in the Adam Optimizer -- Learning Internal Dense But External Sparse Structures of Deep Convolutional Neural Network -- Using feature entropy to guide filter pruning for efficient convolutional networks -- Simultaneously Learning Architectures and Features of Deep Neural Networks -- Learning Sparse Hidden States in Long Short-Term Memory -- Multi-objective Pruning for CNNs using Genetic Algorithm -- Dynamically Sacrificing Accuracy for Reduced Computation: Cascaded Inference Based on Softmax Confidence -- Light-Weight Edge Enhanced Network for On-orbit Semantic Segmentation -- Local Normalization Based BN Layer Pruning -- On Practical Approach to Uniform Quantization of Non-redundant Neural Networks -- Residual learning for FC kernels of convolutional network -- A Novel Neural Network-based Symbolic Regression Method: Neuro-Encoded Expression Programming -- Compute-efficient neural network architecture optimization by a genetic algorithm -- Controlling Model Complexity in Probabilistic Model-Based Dynamic Optimization of Neural Network Structures -- Predictive Uncertainty Estimation with Temporal Convolutional Networks for Dynamic Evolutionary Optimization -- Sparse Recurrent Mixture Density Networks for Forecasting High Variability Time Series with Confidence Estimates -- A multitask learning neural network for short-term traffic speed prediction and confidence estimation -- Central-diffused Instance Generation Method in Class Incremental Learning -- Marginal Replay vs Conditional Replay for Continual Learning -- Simplified computation and interpretation of Fisher matrices in incremental learning with deep neural networks -- Active Learning for Image Recognition using a Visualization-Based User Interface -- Basic Evaluation Scenarios for Incrementally Trained Classifiers -- Embedding Complexity of Learned Representations in Neural Networks -- Joint Metric Learning on Riemannian Manifold of Global Gaussian Distributions -- Multi-Task Sparse Regression Metric Learning for Heterogeneous Classification -- Fast Approximate Geodesics for Deep Generative Models -- Spatial Attention Network for Few-Shot Learning -- Routine Modeling with Time Series Metric Learning -- Leveraging Domain Knowledge for Reinforcement Learning using MMC Architectures -- Conditions for Unnecessary Logical Constraints in Kernel Machines -- HiSeqGAN: Hierarchical Sequence Synthesis and Prediction -- DeepEX: Bridging the Gap Between Knowledge and Data Driven Techniques for Time Series Forecasting -- Transferable Adversarial Cycle Alignment for Domain Adaption -- Evaluation of domain adaptation approaches for robust classification of heterogeneous biological data sets -- Named Entity Recognition for Chinese Social Media with Domain Adversarial Training and Language Modeling -- Deep Domain Knowledge Distillation for Person Re-identification -- A study on catastrophic forgetting in deep LSTM networks -- A Label-specific Attention-based Network with Regularized Loss for Multi-label Classification -- An Empirical Study of Multi-domain and Multi-task Learning in Chinese Named Entity Recognition -- Filter Method Ensemble with Neural Networks -- Dynamic Centroid Insertion and Adjustment for Data Sets with Multiple Imbalanced Classes -- Increasing the Generalisaton Capacity of Conditional VAEs -- Playing the Large Margin Preference Game Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=148040 Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing / Igor V. Tetko ; SpringerLink (Online service) ; Věra Kůrková-Pohlova ; Pavel Karpov ; Fabian Theis / Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer (2019)
Titre : Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing : 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part III Type de document : document électronique Auteurs : Igor V. Tetko, ; SpringerLink (Online service) ; Věra Kůrková-Pohlova, ; Pavel Karpov, ; Fabian Theis, Editeur : Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer Année de publication : 2019 Collection : Lecture Notes in Computer Science - LNCS, ISSN 0302-9743 num. 11729 Importance : XXX, 733 p. 417 illus., 273 illus. in color Présentation : online resource ISBN/ISSN/EAN : 978-3-030-30508-6 Langues : Anglais (eng) Tags : Artificial intelligence Optical data processing Computer organization Computers Algorithms Computer security Artificial Intelligence Image Processing and Computer Vision Computer Systems Organization and Communication Networks Information Systems and Communication Service Algorithm Analysis and Problem Complexity Systems and Data Security Résumé : The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions. Note de contenu : Unsharp Masking Layer: Injecting Prior Knowledge in Convolutional Networks for Image Classification -- Distortion Estimation Through Explicit Modeling of the Refractive Surface -- Eye Movement-based Analysis on Methodologies and Efficiency in the Process of Image Noise Evaluation -- IBDNet: Lightweight Network for On-orbit Image Blind Denoising -- Aggregating Rich Deep Semantic Features for Fine-Grained Place Classification -- Improving Reliability of Object Detection for Lunar Craters using Monte Carlo Dropout -- An improved convolutional neural network for steganalysis in the scenario of reuse of the stego-key -- A New Learning-based One Shot Detection Framework For Natural Images -- Dense Receptive Field Network: A Backbone Network for Object Detection -- Referring Expression Comprehension via Co-attention and Visual Context -- Comparison between U-Net and U-ReNet models in OCR tasks -- Severe Convective Weather Classification in Remote Sensing Images by Semantic Segmentation -- Action Recognition Based on Divide-and-conquer -- An Adaptive Feature Channel Weighting Scheme for Correlation Tracking -- In-silico staining from bright-field and fluorescent images using deep learning -- A lightweight neural network for hard exudate segmentation of fundus image -- Attentional Residual Dense Factorized Network for Real-time Semantic Segmentation -- Random drop loss for tiny object segmentation: Application to lesion segmentation in fundus images -- Flow2Seg: Motion-Aided Semantic Segmentation -- COCO_TS Dataset: Pixel-level Annotations Based on Weak Supervision for Scene Text Segmentation -- Learning Deep Structured Multi-Scale Features for crisp and occlusion edge detection -- Graph-Boosted Attentive Network for Semantic Body Parsing -- A Global-Local Architecture Constrained by Multiple Attributes for Person Re-identification -- Recurrent Connections Aid Occluded Object Recognition by Discounting Occluders -- Learning Relational-Structural Networks for Robust Face Alignment -- An Efficient 3D-NAS Method for Video-based Gesture Recognition -- Robustness of deep LSTM networks in freehand gesture recognition -- Delving into the Impact of Saliency Detector: A GeminiNet for Accurate Saliency Detection -- FCN Salient Object Detection Using Region Cropping -- Object-Level Salience Detection By Progressively Enhanced Network -- Action unit assisted Facial Expression Recognition -- Discriminative Feature Learning using Two-stage Training Strategy for Facial Expression Recognition -- Action Units Classification using ClusWiSARD -- Automatic Estimation of Dog Age: The DogAge Dataset and Challenge -- Neural Network 3D Body Pose Tracking and Prediction for Motion-to-Photon Latency Compensation in Distributed Virtual Reality -- Variational Deep Embedding with Regularized Student-t Mixture Model -- A mixture-of-experts model for vehicle prediction using an online learning approach -- An Application of Convolutional Neural Networks for Analyzing Dogs' Sleep Patterns -- On the Inability of Markov Models to Capture Criticality in Human Mobility -- LSTM with Uniqueness Attention for Human Activity Recognition -- Comparative Research on SOM with Torus and Sphere Topologies for Peculiarity Classification of Flat Finishing Skill Training -- Generative Creativity: Adversarial Learning for Bionic Design -- Self-attention StarGAN for Multi-domain Image-to-image Translation -- Generative Adversarial Networks for Operational Scenario Planing of Renewable Energy Farms: A Study on Wind and Photovoltaic -- Constraint-Based Visual Generation -- Text to Image Synthesis based on Multiple Discrimination -- Disentangling Latent Factors of Variational Auto-Encoder with Whitening -- Training Discriminative Models to Evaluate Generative Ones -- Scene Graph Generation via Convolutional Message Passing and Class-aware Memory Embeddings -- Change Detection in Satellite Images using Reconstruction Errors of Joint Autoencoders -- Physical Adversarial Attacks by Projecting Perturbations -- Improved Forward-backward Propagation to Generate Adversarial Examples -- Incremental Learning of GAN for Detecting Multiple Adversarial Attacks -- Evaluating Defensive Distillation For Defending Text Processing Neural Networks Against Adversarial Examples -- DCT:Differential Combination Testing of Deep Learning Systems -- Restoration as a Defense Against Adversarial Perturbations for Spam Image Detection -- HLR: Generating Adversarial Examples by High-Level Representations Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=147867 Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing : 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part III [document électronique] / Igor V. Tetko, ; SpringerLink (Online service) ; Věra Kůrková-Pohlova, ; Pavel Karpov, ; Fabian Theis, . - Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer, 2019 . - XXX, 733 p. 417 illus., 273 illus. in color : online resource. - (Lecture Notes in Computer Science - LNCS, ISSN 0302-9743; 11729) .
ISBN : 978-3-030-30508-6
Langues : Anglais (eng)
Tags : Artificial intelligence Optical data processing Computer organization Computers Algorithms Computer security Artificial Intelligence Image Processing and Computer Vision Computer Systems Organization and Communication Networks Information Systems and Communication Service Algorithm Analysis and Problem Complexity Systems and Data Security Résumé : The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions. Note de contenu : Unsharp Masking Layer: Injecting Prior Knowledge in Convolutional Networks for Image Classification -- Distortion Estimation Through Explicit Modeling of the Refractive Surface -- Eye Movement-based Analysis on Methodologies and Efficiency in the Process of Image Noise Evaluation -- IBDNet: Lightweight Network for On-orbit Image Blind Denoising -- Aggregating Rich Deep Semantic Features for Fine-Grained Place Classification -- Improving Reliability of Object Detection for Lunar Craters using Monte Carlo Dropout -- An improved convolutional neural network for steganalysis in the scenario of reuse of the stego-key -- A New Learning-based One Shot Detection Framework For Natural Images -- Dense Receptive Field Network: A Backbone Network for Object Detection -- Referring Expression Comprehension via Co-attention and Visual Context -- Comparison between U-Net and U-ReNet models in OCR tasks -- Severe Convective Weather Classification in Remote Sensing Images by Semantic Segmentation -- Action Recognition Based on Divide-and-conquer -- An Adaptive Feature Channel Weighting Scheme for Correlation Tracking -- In-silico staining from bright-field and fluorescent images using deep learning -- A lightweight neural network for hard exudate segmentation of fundus image -- Attentional Residual Dense Factorized Network for Real-time Semantic Segmentation -- Random drop loss for tiny object segmentation: Application to lesion segmentation in fundus images -- Flow2Seg: Motion-Aided Semantic Segmentation -- COCO_TS Dataset: Pixel-level Annotations Based on Weak Supervision for Scene Text Segmentation -- Learning Deep Structured Multi-Scale Features for crisp and occlusion edge detection -- Graph-Boosted Attentive Network for Semantic Body Parsing -- A Global-Local Architecture Constrained by Multiple Attributes for Person Re-identification -- Recurrent Connections Aid Occluded Object Recognition by Discounting Occluders -- Learning Relational-Structural Networks for Robust Face Alignment -- An Efficient 3D-NAS Method for Video-based Gesture Recognition -- Robustness of deep LSTM networks in freehand gesture recognition -- Delving into the Impact of Saliency Detector: A GeminiNet for Accurate Saliency Detection -- FCN Salient Object Detection Using Region Cropping -- Object-Level Salience Detection By Progressively Enhanced Network -- Action unit assisted Facial Expression Recognition -- Discriminative Feature Learning using Two-stage Training Strategy for Facial Expression Recognition -- Action Units Classification using ClusWiSARD -- Automatic Estimation of Dog Age: The DogAge Dataset and Challenge -- Neural Network 3D Body Pose Tracking and Prediction for Motion-to-Photon Latency Compensation in Distributed Virtual Reality -- Variational Deep Embedding with Regularized Student-t Mixture Model -- A mixture-of-experts model for vehicle prediction using an online learning approach -- An Application of Convolutional Neural Networks for Analyzing Dogs' Sleep Patterns -- On the Inability of Markov Models to Capture Criticality in Human Mobility -- LSTM with Uniqueness Attention for Human Activity Recognition -- Comparative Research on SOM with Torus and Sphere Topologies for Peculiarity Classification of Flat Finishing Skill Training -- Generative Creativity: Adversarial Learning for Bionic Design -- Self-attention StarGAN for Multi-domain Image-to-image Translation -- Generative Adversarial Networks for Operational Scenario Planing of Renewable Energy Farms: A Study on Wind and Photovoltaic -- Constraint-Based Visual Generation -- Text to Image Synthesis based on Multiple Discrimination -- Disentangling Latent Factors of Variational Auto-Encoder with Whitening -- Training Discriminative Models to Evaluate Generative Ones -- Scene Graph Generation via Convolutional Message Passing and Class-aware Memory Embeddings -- Change Detection in Satellite Images using Reconstruction Errors of Joint Autoencoders -- Physical Adversarial Attacks by Projecting Perturbations -- Improved Forward-backward Propagation to Generate Adversarial Examples -- Incremental Learning of GAN for Detecting Multiple Adversarial Attacks -- Evaluating Defensive Distillation For Defending Text Processing Neural Networks Against Adversarial Examples -- DCT:Differential Combination Testing of Deep Learning Systems -- Restoration as a Defense Against Adversarial Perturbations for Spam Image Detection -- HLR: Generating Adversarial Examples by High-Level Representations Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=147867 Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series / Igor V. Tetko ; SpringerLink (Online service) ; Věra Kůrková-Pohlova ; Pavel Karpov ; Fabian Theis / Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer (2019)
PermalinkArtificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation / Igor V. Tetko ; SpringerLink (Online service) ; Věra Kůrková-Pohlova ; Pavel Karpov ; Fabian Theis / Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer (2019)
PermalinkArtificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions / Igor V. Tetko ; SpringerLink (Online service) ; Věra Kůrková-Pohlova ; Pavel Karpov ; Fabian Theis / Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer (2019)
PermalinkArtificial Neural Networks - ICANN 2008 / SpringerLink (Online service) / Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer (2008)
PermalinkArtificial Neural Networks - ICANN 2008 / SpringerLink (Online service) / Berlin ; Heidelberg (DEU) ; New York ; Bâle (CHE) : Springer (2008)
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