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 ContentsANN 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.
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