Artificial neural networks - ICANN 2010 : 20th International Conference, Thessaloniki, Greece, September 15-18, 2010 : proceedings
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Artificial neural networks - ICANN 2010 : 20th International Conference, Thessaloniki, Greece, September 15-18, 2010 : proceedings
（Lecture notes in computer science, 6352-6354）
Springer, c2010
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- pt. 2
- pt. 3
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Includes bibliographical references and index
Description and Table of Contents
- Volume
-
pt. 1 ISBN 9783642158186
Description
th This volume is part of the three-volume proceedings of the 20 International Conference on Arti?cial Neural Networks (ICANN 2010) that was held in Th- saloniki, Greece during September 15-18, 2010. ICANN is an annual meeting sponsored by the European Neural Network Society (ENNS) in cooperation with the International Neural Network So- ety (INNS) and the Japanese Neural Network Society (JNNS). This series of conferences has been held annually since 1991 in Europe, covering the ?eld of neurocomputing, learning systems and other related areas. As in the past 19 events, ICANN 2010 provided a distinguished, lively and interdisciplinary discussion forum for researches and scientists from around the globe. Ito?eredagoodchanceto discussthe latestadvancesofresearchandalso all the developments and applications in the area of Arti?cial Neural Networks (ANNs). ANNs provide an information processing structure inspired by biolo- cal nervous systems and they consist of a large number of highly interconnected processing elements (neurons). Each neuron is a simple processor with a limited computing capacity typically restricted to a rule for combining input signals (utilizing an activation function) in order to calculate the output one. Output signalsmaybesenttootherunitsalongconnectionsknownasweightsthatexcite or inhibit the signal being communicated. ANNs have the ability "to learn" by example (a large volume of cases) through several iterations without requiring a priori ?xed knowledge of the relationships between process parameters.
Table of Contents
ANN Applications.- IF-Inference Systems Design for Prediction of Ozone Time Series: The Case of Pardubice Micro-region.- Superior-Order Curvature-Corrected Voltage Reference Using a Current Generator.- A Neural Network-Based Method for Affine 3D Registration of FMRI Time Series Using Fourier Space Subsets.- Neural Networks Regression Inductive Conformal Predictor and Its Application to Total Electron Content Prediction.- Prediction of Compaction Characteristics of Granular Soils by Neural Networks.- Modelling Power Output at Nuclear Power Plant by Neural Networks.- Time Series Forecasting by Evolving Artificial Neural Networks Using "Shuffle", Cross-Validation and Ensembles.- Prediction of Power Consumption for Small Power Region Using Indexing Approach and Neural Network.- Fault Prognosis of Mechanical Components Using On-Line Learning Neural Networks.- Bayesian ANN.- Discovery of Exogenous Variables in Data with More Variables Than Observations.- Bayesian Joint Optimization for Topic Model and Clustering.- An Incremental Bayesian Approach for Training Multilayer Perceptrons.- Application of Semi-Bayesian Neural Networks in the Identification of Load Causing Beam Yielding.- Globally Optimal Structure Learning of Bayesian Networks from Data.- Bio Inspired - Spiking ANN.- Action Potential Bursts Modulate the NMDA-R Mediated Spike Timing Dependent Plasticity in a Biophysical Model.- Cell Microscopic Segmentation with Spiking Neuron Networks.- Investigation of Brain-Computer Interfaces That Apply Sound-Evoked Event-Related Potentials.- Functional Connectivity Driven by External Stimuli in a Network of Hierarchically Organized Neural Modules.- Transmission of Distributed Deterministic Temporal Information through a Diverging/Converging Three-Layers Neural Network.- Noise-Induced Collective Migration for Neural Crest Cells.- Unsupervised Learning of Relations.- Learning Internal Representation of Visual Context in a Neural Coding Network.- Simulating Biological-Inspired Spiking Neural Networks with OpenCL.- Bio-inspired Architecture for Human Detection.- Multilayer and Multipathway Simulation on Retina.- Analysis of Astrophysical Ice Analogs Using Regularized Alternating Least Squares.- A BCI System Based on Orthogonalized EEG Data and Multiple Multilayer Neural Networks in Parallel Form.- Using an Artificial Neural Network to Determine Electrical Properties of Epithelia.- Machine Learning and Personalized Modeling Based Gene Selection for Acute GvHD Gene Expression Data Analysis.- Supervised Associative Learning in Spiking Neural Network.- Biomedical ANN.- Dynamics and Function of a CA1 Model of the Hippocampus during Theta and Ripples.- A Probabilistic Neural Network for Assessment of the Vesicoureteral Reflux's Diagnostic Factors Validity.- Shape-Based Tumor Retrieval in Mammograms Using Relevance-Feedback Techniques.- Efficient Domain Decomposition for a Neural Network Learning Algorithm, Used for the Dose Evaluation in External Radiotherapy.- Towards Better Receptor-Ligand Prioritization: How Machine Learning on Protein-Protein Interaction Data Can Provide Insight Into Receptor-Ligand Pairs.- Computational Neuroscience.- The DAMNED Simulator for Implementing a Dynamic Model of the Network Controlling Saccadic Eye Movements.- A Model of Basal Ganglia in Saccade Generation.- Computational Inferences on Alteration of Neurotransmission in Chemotaxis Learning in Caenorhabditis elegans.- Neuro-symbolic Representation of Logic Programs Defining Infinite Sets.- A Model for Center-Surround Stimulus-Dependent Receptive Fields.- Simple Constraints for Zero-Lag Synchronous Oscillations under STDP.- Feature Selection/Parameter Identification and Dimensionality Reduction.- Multilinear Decomposition and Topographic Mapping of Binary Tensors.- Evolutionary q-Gaussian Radial Basis Functions for Improving Prediction Accuracy of Gene Classification Using Feature Selection.- Sparse Coding for Feature Selection on Genome-Wide Association Data.- Self-adaptive Artificial Neural Network in Numerical Models Calibration.- Measuring Adjective Spaces.- Echo State Networks with Sparse Output Connections.- On Estimating Mutual Information for Feature Selection.- Using Correlation Dimension for Analysing Text Data.- Filtering.- Designing Simple Nonlinear Filters Using Hysteresis of Single Recurrent Neurons for Acoustic Signal Recognition in Robots.- Automatic Segmentation of Color Lip Images Based on Morphological Filter.- Learning in a Unitary Coherent Hippocampus.- Collaborative Filtering through SVD-Based and Hierarchical Nonlinear PCA.- Genetic - Evolutionary Algorithms.- A Novel Tuning Method for Neural Oscillators with a Ladder-Like Structure Based on Oscillation Analysis.- Ensemble-Based Methods for Cancellable Biometrics.- A Privacy-Preserving Distributed and Incremental Learning Method for Intrusion Detection.- Using Evolutionary Multiobjective Techniques for Imbalanced Classification Data.- Modeling the Ase 20 Greek Index Using Artificial Neural Nerworks Combined with Genetic Algorithms.- A Hybrid Approach for Artifact Detection in EEG Data.- Improving the Scalability of Recommender Systems by Clustering Using Genetic Algorithms.- Image - Video and Audio Processing.- A Directional Laplacian Density for Underdetermined Audio Source Separation.- Frontal View Recognition Using Spectral Clustering and Subspace Learning Methods.- Improving the Robustness of Subspace Learning Techniques for Facial Expression Recognition.- Variational Bayesian Image Super-Resolution with GPU Acceleration.- A Novel Approach for Hardware Based Sound Localization.- Color Segmentation Using Self-Organizing Feature Maps (SOFMs) Defined Upon Color and Spatial Image Space.- Independent Component Analysis of Multi-channel Near-Infrared Spectroscopic Signals by Time-Delayed Decorrelation.- Micro Nucleus Detection in Human Lymphocytes Using Convolutional Neural Network.- Region Matching Techniques for Spatial Bag of Visual Words Based Image Category Recognition.- Application of K-Means and MLP in the Automation of Matching of 2DE Gel Images.- Robust Workflow Recognition Using Holistic Features and Outlier-Tolerant Fused Hidden Markov Models.- A Neural Approach to Image Thresholding.- Bubbles Detection on Sea Surface Images.- No-Reference Video Quality Assessment Design Framework Based on Modular Neural Networks.- Removing an Object from Video Sequence Algorithm Implemented on Analog CNN and DSP Microprocessors.
- Volume
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pt. 2 ISBN 9783642158216
Description
th This volume is part of the three-volume proceedings of the 20 International Conference on Arti?cial Neural Networks (ICANN 2010) that was held in Th- saloniki, Greece during September 15-18, 2010. ICANN is an annual meeting sponsored by the European Neural Network Society (ENNS) in cooperation with the International Neural Network So- ety (INNS) and the Japanese Neural Network Society (JNNS). This series of conferences has been held annually since 1991 in Europe, covering the ?eld of neurocomputing, learning systems and other related areas. As in the past 19 events, ICANN 2010 provided a distinguished, lively and interdisciplinary discussion forum for researches and scientists from around the globe. Ito?eredagoodchanceto discussthe latestadvancesofresearchandalso all the developments and applications in the area of Arti?cial Neural Networks (ANNs). ANNs provide an information processing structure inspired by biolo- cal nervous systems and they consist of a large number of highly interconnected processing elements (neurons). Each neuron is a simple processor with a limited computing capacity typically restricted to a rule for combining input signals (utilizing an activation function) in order to calculate the output one. Output signalsmaybesenttootherunitsalongconnectionsknownasweightsthatexcite or inhibit the signal being communicated. ANNs have the ability "to learn" by example (a large volume of cases) through several iterations without requiring a priori ?xed knowledge of the relationships between process parameters.
Table of Contents
Kernel Algorithms - Support Vector Machines.- Convergence Improvement of Active Set Training for Support Vector Regressors.- The Complex Gaussian Kernel LMS Algorithm.- Support Vector Machines-Kernel Algorithms for the Estimation of the Water Supply in Cyprus.- Faster Directions for Second Order SMO.- Almost Random Projection Machine with Margin Maximization and Kernel Features.- A New Tree Kernel Based on SOM-SD.- Kernel-Based Learning from Infinite Dimensional 2-Way Tensors.- Semi-supervised Facial Expressions Annotation Using Co-Training with Fast Probabilistic Tri-Class SVMs.- An Online Incremental Learning Support Vector Machine for Large-scale Data.- A Common Framework for the Convergence of the GSK, MDM and SMO Algorithms.- The Support Feature Machine for Classifying with the Least Number of Features.- Knowledge Engineering and Decision Making.- Hidden Markov Model for Human Decision Process in a Partially Observable Environment.- Representing, Learning and Extracting Temporal Knowledge from Neural Networks: A Case Study.- Recurrent ANN.- Multi-Dimensional Deep Memory Atari-Go Players for Parameter Exploring Policy Gradients.- Layered Motion Segmentation with a Competitive Recurrent Network.- Selection of Training Data for Locally Recurrent Neural Network.- A Statistical Appraoch to Image Reconstruction from Projections Problem Using Recurrent Neural Network.- A Computational System of Metaphor Generation with Evaluation Mechanism.- Recurrence Enhances the Spatial Encoding of Static Inputs in Reservoir Networks.- Action Classification in Soccer Videos with Long Short-Term Memory Recurrent Neural Networks.- Reinforcement Learning.- A Hebbian-Based Reinforcement Learning Framework for Spike-Timing-Dependent Synapses.- An Incremental Probabilistic Neural Network for Regression and Reinforcement Learning Tasks.- Using Reinforcement Learning to Guide the Development of Self-organised Feature Maps for Visual Orienting.- Exploring Continuous Action Spaces with Diffusion Trees for Reinforcement Learning.- An Alternative Approach to the Revision of Ordinal Conditional Functions in the Context of Multi-Valued Logic.- One-Shot Supervised Reinforcement Learning for Multi-targeted Tasks: RL-SAS.- An Oscillatory Neural Network Model for Birdsong Learning and Generation.- A Computational Neuromotor Model of the Role of Basal Ganglia and Hippocampus in Spatial Navigation.- Reinforcement Learning Based Neural Controllers for Dynamic Processes without Exploration.- A Neurocomputational Model of Nicotine Addiction Based on Reinforcement Learning.- Robotics.- Teaching Humanoids to Imitate 'Shapes' of Movements.- The Dynamics of a Neural Network of Coupled Phase Oscillators with Synaptic Plasticity Controlling a Minimally Cognitive Agent.- Integrative Learning between Language and Action: A Neuro-Robotics Experiment.- Sliding Mode Control of Robot Based on Neural Network Model with Positive Definite Inertia Matrix.- Hardware Implementation of a CPG-Based Locomotion Control for Quadruped Robots.- Evolutionary Strategies Used for the Mobile Robot Trajectory Tracking Control.- A Novel Topological Map of Place Cells for Autonomous Robots.- Hybrid Control Structure for Multi-robot Formation.- From Conditioning of a Non Specific Sensor to Emotional Regulation of Behavior.- A Robot Vision Algorithm for Navigating in and Creating a Topological Map of a Reconfigurable Maze.- Self Organizing ANN.- Generation of Comprehensible Representations by Supposed Maximum Information.- Visualization of Changes in Process Dynamics Using Self-Organizing Maps.- Functional Architectures and Hierarchies of Time Scales.- A Novel Single-Trial Analysis Scheme for Characterizing the Presaccadic Brain Activity Based on a SON Representation.- Web Spam Detection by Probability Mapping GraphSOMs and Graph Neural Networks.- Self-Organizing Maps for Improving the Channel Estimation and Predictive Modelling Phase of Cognitive Radio Systems.- Application of SOM-Based Visualization Maps for Time-Response Analysis of Industrial Processes.- Snap-Drift Self Organising Map.- Fault Severity Estimation in Rotating Mechanical Systems Using Feature Based Fusion and Self-Organizing Maps.- Self-Organization of Steerable Topographic Mappings as Basis for Translation Invariance.- A Self-Organizing Map for Controlling Artificial Locomotion.- Visualising Clusters in Self-Organising Maps with Minimum Spanning Trees.- Elementary Logical Reasoning in the SOM Output Space.- Adaptive Algorithms - Systems.- Adaptive Critic Design with ESN Critic for Bioprocess Optimization.- Correcting Errors in Optical Data Transmission Using Neural Networks.- Adaptive Classifiers with ICI-Based Adaptive Knowledge Base Management.- Multi Class Semi-Supervised Classification with Graph Construction Based on Adaptive Metric Learning.- Genetically Tuned Controller of an Adaptive Cruise Control for Urban Traffic Based on Ultrasounds.- Adaptive Local Fusion with Neural Networks.- A Controlling Strategy for an Active Vision System Based on Auditory and Visual Cues.- Optimization.- A One-Layer Dual Neural Network with a Unipolar Hard-Limiting Activation Function for Shortest-Path Routing.- Optimizing Hierarchical Temporal Memory for Multivariable Time Series.- Solving Independent Component Analysis Contrast Functions with Particle Swarm Optimization.- Binary Minimization: Increasing the Attraction Area of the Global Minimum in the Binary Optimization Problem.- An Artificial Immune Network for Multi-objective Optimization.
by "Nielsen BookData"