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Advances in Neural Networks – ISNN 2016 [[electronic resource] ] : 13th International Symposium on Neural Networks, ISNN 2016, St. Petersburg, Russia, July 6-8, 2016, Proceedings / / edited by Long Cheng, Qingshan Liu, Andrey Ronzhin
| Advances in Neural Networks – ISNN 2016 [[electronic resource] ] : 13th International Symposium on Neural Networks, ISNN 2016, St. Petersburg, Russia, July 6-8, 2016, Proceedings / / edited by Long Cheng, Qingshan Liu, Andrey Ronzhin |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XX, 741 p. 278 illus.) |
| Disciplina | 006.4 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Pattern recognition systems
Algorithms Artificial intelligence Computer science—Mathematics Neural networks (Computer science) Data protection Automated Pattern Recognition Artificial Intelligence Mathematics of Computing Mathematical Models of Cognitive Processes and Neural Networks Data and Information Security |
| ISBN | 3-319-40663-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Signal and image processing -- Dynamical behaviors of recurrent neural networks -- Intelligent control.-Clustering, classification, modeling, and forecasting -- Evolutionary computation -- Cognition computation and spiking neural networks. |
| Record Nr. | UNISA-996465960603316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in Neural Networks – ISNN 2016 : 13th International Symposium on Neural Networks, ISNN 2016, St. Petersburg, Russia, July 6-8, 2016, Proceedings / / edited by Long Cheng, Qingshan Liu, Andrey Ronzhin
| Advances in Neural Networks – ISNN 2016 : 13th International Symposium on Neural Networks, ISNN 2016, St. Petersburg, Russia, July 6-8, 2016, Proceedings / / edited by Long Cheng, Qingshan Liu, Andrey Ronzhin |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XX, 741 p. 278 illus.) |
| Disciplina | 006.4 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Pattern recognition systems
Algorithms Artificial intelligence Computer science—Mathematics Neural networks (Computer science) Data protection Automated Pattern Recognition Artificial Intelligence Mathematics of Computing Mathematical Models of Cognitive Processes and Neural Networks Data and Information Security |
| ISBN | 3-319-40663-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Signal and image processing -- Dynamical behaviors of recurrent neural networks -- Intelligent control.-Clustering, classification, modeling, and forecasting -- Evolutionary computation -- Cognition computation and spiking neural networks. |
| Record Nr. | UNINA-9910484031003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computer Vision : Second CCF Chinese Conference, CCCV 2017, Tianjin, China, October 11–14, 2017, Proceedings, Part II / / edited by Jinfeng Yang, Qinghua Hu, Ming-Ming Cheng, Liang Wang, Qingshan Liu, Xiang Bai, Deyu Meng
| Computer Vision : Second CCF Chinese Conference, CCCV 2017, Tianjin, China, October 11–14, 2017, Proceedings, Part II / / edited by Jinfeng Yang, Qinghua Hu, Ming-Ming Cheng, Liang Wang, Qingshan Liu, Xiang Bai, Deyu Meng |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XXIII, 621 p. 274 illus.) |
| Disciplina | 006.37 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Optical data processing
Artificial intelligence Computer simulation Data mining Information storage and retrieval Image Processing and Computer Vision Artificial Intelligence Simulation and Modeling Data Mining and Knowledge Discovery Information Storage and Retrieval |
| ISBN | 981-10-7302-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Biological vision inspired visual method -- Biomedical image analysis -- Computer vision applications -- Deep neural network -- Face and posture analysis -- Image and video retrieval -- Image color and texture -- Image composition -- Image quality assessment and analysis -- Image restoration -- Image segmentation and classification -- Image-based modeling -- Object detection and classification -- Object identification -- Photography and video -- Robot vision -- Shape representation and matching -- Statistical methods and learning.-Video analysis and event recognition.-Visual salient detection. |
| Record Nr. | UNINA-9910254837603321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computer Vision : Second CCF Chinese Conference, CCCV 2017, Tianjin, China, October 11–14, 2017, Proceedings, Part I / / edited by Jinfeng Yang, Qinghua Hu, Ming-Ming Cheng, Liang Wang, Qingshan Liu, Xiang Bai, Deyu Meng
| Computer Vision : Second CCF Chinese Conference, CCCV 2017, Tianjin, China, October 11–14, 2017, Proceedings, Part I / / edited by Jinfeng Yang, Qinghua Hu, Ming-Ming Cheng, Liang Wang, Qingshan Liu, Xiang Bai, Deyu Meng |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XXIV, 771 p. 373 illus.) |
| Disciplina | 006.37 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Optical data processing
Artificial intelligence Computer simulation Data mining Information storage and retrieval Pattern recognition Image Processing and Computer Vision Artificial Intelligence Simulation and Modeling Data Mining and Knowledge Discovery Information Storage and Retrieval Pattern Recognition |
| ISBN | 981-10-7299-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Biological vision inspired visual method -- Biomedical image analysis -- Computer vision applications -- Deep neural network -- Face and posture analysis -- Image and video retrieval.-Image color and texture -- Image composition -- Image quality assessment and analysis -- Image restoration -- Image segmentation and classification -- Image-based modeling -- Object detection and classification -- Object identification -- Photography and video -- Robot vision -- Shape representation and matching -- Statistical methods and learning.-Video analysis and event recognition.-Visual salient detection. |
| Record Nr. | UNINA-9910254837503321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computer Vision : Second CCF Chinese Conference, CCCV 2017, Tianjin, China, October 11–14, 2017, Proceedings, Part III / / edited by Jinfeng Yang, Qinghua Hu, Ming-Ming Cheng, Liang Wang, Qingshan Liu, Xiang Bai, Deyu Meng
| Computer Vision : Second CCF Chinese Conference, CCCV 2017, Tianjin, China, October 11–14, 2017, Proceedings, Part III / / edited by Jinfeng Yang, Qinghua Hu, Ming-Ming Cheng, Liang Wang, Qingshan Liu, Xiang Bai, Deyu Meng |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XXIII, 729 p. 345 illus.) |
| Disciplina | 006.37 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Optical data processing
Artificial intelligence Computer simulation Data mining Information storage and retrieval Image Processing and Computer Vision Artificial Intelligence Simulation and Modeling Data Mining and Knowledge Discovery Information Storage and Retrieval |
| ISBN | 981-10-7305-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Biological vision inspired visual method -- Biomedical image analysis -- Computer vision applications -- Deep neural network -- Face and posture analysis -- Image and video retrieval -- Image color and texture -- Image composition -- Image quality assessment and analysis -- Image restoration -- Image segmentation and classification -- Image-based modeling -- Object detection and classification -- Object identification -- Photography and video -- Robot vision -- Shape representation and matching -- Statistical methods and learning.-Video analysis and event recognition.-Visual salient detection. |
| Record Nr. | UNINA-9910254843903321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Neural Information Processing [[electronic resource] ] : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015, Proceedings Part III / / edited by Sabri Arik, Tingwen Huang, Weng Kin Lai, Qingshan Liu
| Neural Information Processing [[electronic resource] ] : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015, Proceedings Part III / / edited by Sabri Arik, Tingwen Huang, Weng Kin Lai, Qingshan Liu |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XVII, 710 p. 250 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Pattern recognition systems
Computer vision Artificial intelligence Computer science Data mining Application software Automated Pattern Recognition Computer Vision Artificial Intelligence Theory of Computation Data Mining and Knowledge Discovery Computer and Information Systems Applications |
| ISBN | 3-319-26555-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part III -- Design of an Adaptive Support Vector Regressor Controller for a Spherical Tank System -- 1 Introduction -- 2 Adaptive Online SVR Controller -- 3 Online -SVR for Controller Design -- 4 Simulation Results -- 5 Conclusion -- References -- Robust Tracking Control of Uncertain Nonlinear Systems Using Adaptive Dynamic Programming -- 1 Introduction -- 2 Preliminaries -- 3 Problem Transformation -- 4 Approximate the HJB Solution via ADP -- 5 Simulation Results -- 6 Conclusions -- References -- Moving Target Tracking Based on Pulse Coupled Neural Network and Optical Flow -- Abstract -- 1 Introduction -- 2 Related Work -- 2.1 Optical Flow -- 2.2 Pulse-Coupled Neural Network -- 2.3 PCNN Fusion Based on Optical Flow -- 2.4 Topological Property -- 3 Algorithm Structure -- 4 Experimental Results -- 4.1 Database -- 4.2 Attention Detection Effects -- 4.3 Comparison of Attention Detection Models -- 5 Conclusion -- References -- Efficient Motor Babbling Using Variance Predictions from a Recurrent Neural Network -- 1 Introduction -- 2 Exploratory Motor Babbling -- 2.1 Stochastic Continuous Time-Scales Recurrent Neural Networks -- 2.2 Learning Process of Exploratory Motor Babbling -- 3 Experimental Setup -- 3.1 Robot Model in Simulation -- 3.2 Design of Motor Babbling -- 3.3 Experimental Evaluation -- 4 Experimental Results and Discussion -- 5 Conclusion -- References -- Distributed Control for Nonlinear Time-Delayed Multi-Agent Systems with Connectivity Preservation Using Neural Networks -- 1 Introduction -- 2 Preliminaries -- 2.1 Graph Theory -- 2.2 Radial Basis Function Neural Network -- 2.3 Problem Statement -- 3 Distributed Control for Nonlinear Time-Delayed Multi-Agent Systems -- 4 Simulation Example -- 5 Conclusion -- References.
Coevolutionary Recurrent Neural Networks for Prediction of Rapid Intensification in Wind Intensity of Tropical Cyclones in the South Pacific Region -- 1 Introduction -- 2 Coevolutionary Recurrent Networks for Rapid Intensification -- 2.1 Recurrent Network Architecture -- 2.2 Cooperative Neuro-Evolutionary Recurrent Networks -- 2.3 Application Problem: Rapid intensification in Cyclones -- 3 Experiments and Results -- 3.1 Analysis of the Dataset -- 3.2 Data Pre-processing -- 3.3 Results -- 3.4 Discussion -- 4 Conclusions and Future Work -- References -- Nonlinear Filtering Based on a Network with Gaussian Kernel Functions -- 1 Introduction -- 2 Nonlinear Filters for Signal Enhancement -- 3 Phase Space Analysis of Noisy Signals -- 4 Nonlinear Filters with Gaussian Kernel Functions -- 5 Simulation -- 6 Conclusion -- References -- Computing Skyline Probabilities on Uncertain Time Series -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Background of Skyline Queries -- 3.1 Skylines on Certain Time Series -- 3.2 Skylines on Uncertain Time Series -- 4 Probabilistic Skyline Answering Algorithm -- 4.1 Obtaining the Skyline -- 4.2 Computing the Skyline Probability -- 5 Experiment Study -- 6 Conclusions -- References -- Probabilistic Prediction of Chaotic Time Series Using Similarity of Attractors and LOOCV Predictable Horizons for Obtaining Plausible Predictions -- 1 Introduction -- 2 Probabilistic Prediction of Chaotic Time Series -- 2.1 Point Prediction of Chaotic Time Series -- 2.2 Probabilistic Prediction -- 3 Numerical Experiments and Analysis -- 3.1 Experimental Settings -- 3.2 Results and Analysis -- 4 Conclusion -- A CAN2 -- References -- Adaptive Threshold for Anomaly Detection Using Time Series Segmentation -- 1 Introduction -- 2 Segmentation and Anomaly Detection -- 3 Adaptive Threshold for Anomaly Detection (ATAD). 3.1 Adaptive Piecewise Constant Approximation -- 3.2 Description of the Method -- 3.3 Numerical Experiments -- 4 Conclusion and Future Works -- References -- Neuron-Synapse Level Problem Decomposition Method for Cooperative Neuro-Evolution of Feedforward Networks for Time Series Prediction -- 1 Introduction -- 2 Neuron-Synapse Level Problem Decomposition -- 3 Experiments, Results and Discussion -- 3.1 Experimental Setup -- 3.2 Results -- 3.3 Discussion -- 4 Conclusions -- References -- Prediction Interval-Based Control of Nonlinear Systems Using Neural Networks -- 1 Introduction -- 2 PI-based Controller -- 3 Proposed Methodology -- 3.1 Feed-Forward NN Model -- 3.2 PI-based NN Model -- 3.3 PI-based NN Inverse Model (PIC) -- 4 Case Studies -- 5 Results and Discussion -- 6 Conclusion -- References -- Correcting a Class of Complete Selection Bias with External Data Based on Importance Weight Estimation -- 1 Introduction -- 2 Bias Correction -- 3 Experiments -- 3.1 Toy Problem -- 3.2 Real-World Data Sets -- 4 Discussion and Conclusion -- References -- Lagrange Programming Neural Network for the l1-norm Constrained Quadratic Minimization -- 1 Introduction -- 2 Background -- 3 LPNN for L1CQM -- 4 Properties of LPNN -- 5 Simulations -- 6 Conclusion -- References -- Multi-Island Competitive Cooperative Coevolution for Real Parameter Global Optimization -- 1 Introduction -- 2 Multi-Island Competitive Cooperative Coevolution -- 2.1 Initialization -- 2.2 Cooperative Coevolution -- 2.3 Competition -- 2.4 Collaboration - Solution Migration -- 3 Simulation and Analysis -- 3.1 Benchmark Problems and Configuration -- 3.2 Results and Analysis -- 3.3 Discussion -- 4 Conclusions and Future Work -- References -- Competitive Island-Based Cooperative Coevolution for Efficient Optimization of Large-Scale Fully-Separable Continuous Functions -- 1 Introduction. 2 Competitive Island Cooperative Coevolution for Fully-Separable Continuous Functions -- 2.1 Initialization -- 2.2 Coevolution in CICC -- 2.3 Competition and Collaboration -- 3 Simulation and Analysis -- 3.1 Problem Decomposition Strategies -- 3.2 Benchmark Problems and Parameter Settings -- 4 Results and Analyses -- 4.1 Competition Between Same Problem Decomposition Strategies -- 4.2 Competition Between Different Problem Decomposition Strategies -- 5 Conclusions and Future Work -- References -- Topic Optimization Method Based on Pointwise Mutual Information -- Abstract -- 1 Introduction -- 2 LDA Based on Point-Wise Mutual Information (PMI-LDA) -- 2.1 Introduction of the LDA Topic Model -- 2.2 PMI-LDA Topic Model -- 3 Topic Evaluation -- 4 Experiments -- 5 Conclusion -- Acknowledgments -- References -- Optimization and Analysis of Parallel Back Propagation Neural Network on GPU Using CUDA -- Abstract -- 1 Introduction -- 2 Parallel Back Propagation Algorithm on GPU -- 3 Optimized Program Framework on GPU -- 4 Experimental Results and Discussion -- 4.1 Data Sets for Experiments -- 4.2 Results of Experiments -- 4.3 Discussion -- 5 Conclusions -- References -- Objective Function of ICA with Smooth Estimation of Kurtosis -- 1 Introduction -- 2 Derivation of Objective Function of ICA -- 2.1 Preliminaries -- 2.2 Estimation of True Distribution -- 2.3 Objective Function -- 3 Optimization Method -- 4 Results -- 5 Conclusion -- References -- FANet: Factor Analysis Neural Network -- 1 Introduction -- 2 Unsupervised Feature Learning via FANet -- 2.1 Normalizing the Input Data -- 2.2 Convolution Layers -- 2.3 Pooling Layers -- 2.4 Analytical Characterization of FANet -- 3 Experiments -- 3.1 Facial Recognition on FERET -- 3.2 Handwritten Digit Recognition on MNIST and MNIST Variations -- 4 Conclusion -- References. Oscillated Variable Neighborhood Search for Open Vehicle Routing Problem -- Abstract -- 1 Introduction -- 2 Proposed Algorithm -- 3 Experimental Results -- 4 Conclusion -- Acknowledgements -- References -- Non-Line-of-Sight Mitigation via Lagrange Programming Neural Networks in TOA-Based Localization -- 1 Introduction -- 2 Background -- 2.1 Problem Formulation -- 3 Algorithm Development -- 4 Simulation Results -- 5 Conclusion -- References -- Wave-Based Reservoir Computing by Synchronization of Coupled Oscillators -- 1 Introduction -- 2 Wave-Based Reservoir Computing -- 3 Phase Dynamics of Coupled Oscillators -- 3.1 Phase Response Curves -- 3.2 Phase Synchronization -- 4 Function Approximation and Regression by Wave-Based Reservoir Computing -- 4.1 Function Approximation by Two Coupled Oscillators -- 4.2 Functional Regression by an Oscillator Reservoir -- 5 Conclusion -- References -- Hybrid Controller with the Combination of FLC and Neural Network-Based IMC for Nonlinear Processes -- 1 Introduction -- 2 Proposed Hybrid Controller -- 2.1 Fuzzy Logic Controller -- 2.2 NN-Based Internal Model Controller -- 2.3 Hybrid Controller -- 3 Methodology -- 3.1 Development of FLC -- 3.2 Development of NN-Based IMC -- 4 Case Study and Experimental Data -- 5 Results and Discussion -- 6 Conclusion -- References -- Comparative Study of Web-Based Gene Expression Analysis Tools for Biomarkers Identification -- Abstract -- 1 Introduction -- 2 Methodology -- 2.1 Gene Expression Datasets -- 2.2 Web-Based Gene Expression Analysis Tools -- 2.3 Evaluation -- 3 Results and Discussion -- 3.1 Features Comparison -- 3.2 Gene Markers Comparison -- 3.3 Classification of Selected Gene Markers -- 4 Conclusion -- References -- Eye Can Tell: On the Correlation Between Eye Movement and Phishing Identification -- 1 Introduction -- 2 Related Work -- 3 Proposal -- 4 Experiment Setup. 5 Eye Movement Analysis. |
| Record Nr. | UNISA-996466217203316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Neural Information Processing [[electronic resource] ] : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015, Proceedings, Part I / / edited by Sabri Arik, Tingwen Huang, Weng Kin Lai, Qingshan Liu
| Neural Information Processing [[electronic resource] ] : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015, Proceedings, Part I / / edited by Sabri Arik, Tingwen Huang, Weng Kin Lai, Qingshan Liu |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XVII, 742 p. 251 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Pattern recognition systems
Computer vision Artificial intelligence Computer science Data mining Application software Automated Pattern Recognition Computer Vision Artificial Intelligence Theory of Computation Data Mining and Knowledge Discovery Computer and Information Systems Applications |
| ISBN | 3-319-26532-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part I -- Texture Classification with Patch Autocorrelation Features -- 1 Introduction -- 2 Related Work -- 3 Translation and Rotation Invariant Patch Autocorrelation Features -- 3.1 Texture Features -- 4 Texture Classification Experiments -- 4.1 Data Set -- 4.2 Learning Methods -- 4.3 Implementation and Evaluation -- 4.4 Parameter Tuning -- 4.5 Results on Brodatz Data Set -- 5 Conclusion -- References -- Novel Architecture for Cellular Neural Network Suitable for High-Density Integration of Electron Dev ... -- Abstract -- 1 Introduction -- 2 Device Architecture -- 2.1 Neuron -- 2.2 Synapse -- 2.3 Network -- 3 Learning Principle -- 4 Fabrication Process -- 5 Experimental Result -- 6 Conclusion -- References -- Analyzing the Impact of Feature Drifts in Streaming Learning -- 1 Introduction -- 2 Problem Statement -- 3 Simulating Feature Drifts -- 4 Analysis -- 4.1 Evaluated Algorithms -- 4.2 Experimental Protocol -- 4.3 Results Obtained -- 5 Conclusion -- References -- Non-linear Metric Learning Using Metric Tensor -- Abstract -- 1 Introduction -- 2 Theoretical Analysis -- 3 Problem Simplification -- 4 Algorithm -- 5 Experiment -- 5.1 Performance in Supervised Metric Learning -- 5.2 Application in Semi-supervised Clustering -- 6 Conclusion -- References -- An Optimized Second Order Stochastic Learning Algorithm for Neural Network Training -- 1 Introduction -- 2 Proposed Algorithm -- 2.1 Overview of Learning Algorithms -- 2.2 Stochastic Diagonal Levenberg-Marquardt Algorithm -- 2.3 Bounded SDLM Algorithm -- 3 Experimental Design -- 4 Results and Discussions -- 5 Conclusion and Future Works -- References -- Max-Pooling Dropout for Regularization of Convolutional Neural Networks -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Max-Pooling Dropout -- 3.1 Max-Pooling Dropout at Training Time.
3.2 Probabilistic Weighted Pooling at Test Time -- 4 Empirical Evaluations -- 4.1 Probabilistic Weighted Pooling vs. (Scaled) Max-Pooling -- 4.2 Max-Pooling Dropout vs. Stochastic Pooling -- 5 Conclusions -- References -- Predicting Box Office Receipts of Movies with Pruned Random Forest -- 1 Introduction -- 2 Methodology -- 2.1 Movie Information Data Collection -- 2.2 Pruned Random Forest -- 2.3 Advice for Screen Schedule -- 3 Results -- 3.1 The Classification Performance of Pruned Random Forest -- 3.2 Comparison with Other Models -- 4 Conclusion -- References -- A Novel 1-graph Based Image Classification Algorithm -- 1 Introduction -- 2 Background -- 2.1 Sparse Representation Based Classification Algorithm -- 2.2 1-Graph -- 3 1-graph Based Image Classification Method -- 3.1 Relationship Between Training Samples and Classes -- 3.2 Classification Process -- 4 Experiment Results -- 4.1 Face Recognition -- 4.2 Handwritten Digit Recognition -- 5 Conclusion and Future Work -- References -- Classification of Keystroke Patterns for User Identification in a Pressure-Based Typing Biometrics S ... -- Abstract -- 1 Introduction -- 2 System Design -- 2.1 Force Sensor -- 2.2 Microprocessor Design with Arduino -- 3 Classification -- 3.1 Particle Swarm Optimization -- 3.2 K-Means -- 4 Experimental Setup and Results -- 5 Conclusions -- References -- Discriminative Orthonormal Dictionary Learning for Fast Low-Rank Representation -- 1 Introduction -- 2 Discriminative Orthonormal Dictionary Learning -- 2.1 Formulation -- 2.2 Optimization -- 3 Fast Low-Rank Representation -- 4 Experiments -- 4.1 Extended Yale B Dataset -- 4.2 AR Dataset -- 4.3 Caltech 101 Dataset -- 5 Conclusions -- References -- Supervised Topic Classification for Modeling a Hierarchical Conference Structure -- 1 Introduction -- 2 Supervised Classification, Flat Case -- 3 Topics Hierarchy. 4 Empirical Results -- 5 Conclusion -- References -- A Framework for Online Inter-subjects Classification in Endogenous Brain-Computer Interfaces -- Abstract -- 1 Introduction -- 2 Methods -- 2.1 Base Classifiers' Weights Initialization -- 2.2 Base Classifiers' Weights Adaptation Using Ensemble Predictions -- 2.3 Base Classifiers' Weights Adaptation Using Ensemble Predictions Reinforced by Interaction Error-Related Potentials -- 3 Experiments -- 3.1 EEG Data Sets -- 3.2 Procedure for Simulating IErrPs -- 3.3 Results -- 4 Conclusion -- References -- A Bayesian Sarsa Learning Algorithm with Bandit-Based Method -- 1 Introduction -- 2 Bayesian Sarsa -- 2.1 Q-values Distribution -- 2.2 Updating Q-Values -- 2.3 Actions Selection -- 3 Experimental Results -- 3.1 Gridworld -- 4 Conclusion -- References -- Incrementally Built Dictionary Learning for Sparse Representation -- 1 Introduction -- 2 Background on Dictionary Learning -- 3 Incrementally Built Dictionary Learning -- 3.1 Approach Description -- 3.2 Incremental Learning Rule -- 3.3 Sparse Coding-Based Feature Extraction -- 4 Experimentations -- 4.1 Digits Recognition -- 4.2 Face Recognition -- 4.3 The Effects of Incremental Learning -- 5 Conclusion -- References -- Learning to Reconstruct 3D Structure from Object Motion -- 1 Introduction -- 2 Related Work -- 3 DNN Based 3D Reconstruction Method -- 3.1 Reconstruction Unit -- 3.2 Deep Neural Network for 3D Reconstruction -- 3.3 Temporal Integration -- 4 Experiments -- 4.1 Data Generation -- 4.2 Reconstruction on Synthetic Images -- 4.3 Reconstruction on Real Images -- 5 Conclusions -- References -- Convolutional Networks Based Edge Detector Learned via Contrast Sensitivity Function -- 1 Introduction -- 2 The Model Architecture -- 2.1 Convolutional Networks -- 2.2 Multi-channel Structure -- 3 Training Data Generation and Annotation. 3.1 Training Data Generation -- 3.2 Training Data Annotation -- 4 Experiments -- 5 Conclusion -- References -- Learning Algorithms and Frame Signatures for Video Similarity Ranking -- 1 Introduction -- 2 Similar-Video Retrieval -- 2.1 Frame Features -- 2.2 Clustering Algorithms for Exemplar Extraction -- 2.3 Global and Local Alignments -- 3 Video Signature Tools -- 3.1 Frame Signature -- 3.2 Word and Bag of Words -- 4 Experiments on Video Similarity Ranking -- 4.1 Test Video Set and Evaluation Method -- 4.2 Experimental Results -- 5 Discussions -- References -- On Measuring the Complexity of Classification Problems -- 1 Introduction -- 2 Complexity Measures/Indices -- 2.1 Feature/Attribute Overlapping -- 2.2 Separability of Classes -- 2.3 Geometry, Topology and Density -- 3 Conclusion -- References -- The Effect of Stemming and Stop-Word-Removal on Automatic Text Classification in Turkish Language -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 4 Methodology for Dataset -- 5 The Experimental Results -- 6 Conclusion -- References -- Example-Specific Density Based Matching Kernel for Classification of Varying Length Patterns of Speech Using Support Vector Machines -- 1 Introduction -- 2 Dynamic Kernels for Sets of Feature Vectors -- 3 Example-Specific Density Based Matching Kernel for Sets of Feature Vectors -- 4 Experimental Studies on Speech Emotion Recognition and Speaker Identification -- 5 Conclusions -- References -- Possibilistic Information Retrieval Model Based on Relevant Annotations and Expanded Classification -- Abstract -- 1 Introduction -- 2 Related Works -- 3 Filtering Annotation Approach -- 4 Classification of Annotations -- 4.1 Initial Classification -- 4.2 Clusters Extension -- 5 Experimental Evaluation and Analysis of Results -- 5.1 Used Collection of Data -- 5.2 Effects of the Classified and Filtered Annotation. 6 Conclusion and Future Works -- References -- A Transfer Learning Method with Deep Convolutional Neural Network for Diffuse Lung Disease Classification -- 1 Introduction -- 2 Methods -- 2.1 Deep Convolutional Neural Network (DCNN) -- 2.2 Transfer Learning for DCNN -- 2.3 Materials -- 3 Results -- 4 Summary and Discussion -- References -- Evaluation of Machine Learning Algorithms for Automatic Modulation Recognition -- Abstract -- 1 Introduction -- 2 System Model, Signal and Channel Representation -- 3 Feature Extraction -- 3.1 Spectral Features -- 3.2 Statistical Features -- 4 Nonnegative Matrix Factorization (NMF) -- 5 Experimental Results -- 6 Conclusion -- References -- Probabilistic Prediction in Multiclass Classification Derived for Flexible Text-Prompted Speaker Verification -- 1 Introduction -- 2 Probabilistic Prediction for Text-Prompted Speaker Verification -- 2.1 Multistep Speaker and Text Verification Using GEBI -- 2.2 Probabilistic Prediction for Speaker and Text Verification -- 2.3 Loss Functions for Evaluating the Performance -- 3 Experiments -- 3.1 Experimental Setting -- 3.2 Experimental Results and Analysis -- 4 Conclusion -- References -- Simple Feature Quantities for Learning of Dynamic Binary Neural Networks -- 1 Introduction -- 2 Dynamic Binary Neural Networks -- 3 Teacher Signal and Feature Quantities -- 4 Greedy Search Based Sparsification Algorithm -- 5 Conclusions -- References -- Transfer Metric Learning for Kinship Verification with Locality-Constrained Sparse Features -- 1 Introduction -- 2 Proposed Approach -- 2.1 Feature Extraction -- 2.2 NRTML -- 3 Experiments -- 3.1 Experimental Settings -- 3.2 Experimental Results -- 4 Conclusion -- References -- Unsupervised Land Classification by Self-organizing Map Utilizing the Ensemble Variance Information in Satellite-Borne Polarimetric Synthetic Aperture Radar. 1 Introduction. |
| Record Nr. | UNISA-996466222003316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Neural Information Processing [[electronic resource] ] : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015, Proceedings, Part II / / edited by Sabri Arik, Tingwen Huang, Weng Kin Lai, Qingshan Liu
| Neural Information Processing [[electronic resource] ] : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015, Proceedings, Part II / / edited by Sabri Arik, Tingwen Huang, Weng Kin Lai, Qingshan Liu |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XVI, 666 p. 229 illus.) |
| Disciplina | 006.32 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Pattern recognition systems
Computer vision Artificial intelligence Computer science Data mining Application software Automated Pattern Recognition Computer Vision Artificial Intelligence Theory of Computation Data Mining and Knowledge Discovery Computer and Information Systems Applications |
| ISBN | 3-319-26535-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996466222203316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Neural Information Processing [[electronic resource] ] : 22nd International Conference, ICONIP 2015, November 9-12, 2015, Proceedings, Part IV / / edited by Sabri Arik, Tingwen Huang, Weng Kin Lai, Qingshan Liu
| Neural Information Processing [[electronic resource] ] : 22nd International Conference, ICONIP 2015, November 9-12, 2015, Proceedings, Part IV / / edited by Sabri Arik, Tingwen Huang, Weng Kin Lai, Qingshan Liu |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XVII, 702 p. 257 illus.) |
| Disciplina | 006.32 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Pattern recognition systems
Computer vision Artificial intelligence Computer science Data mining Application software Automated Pattern Recognition Computer Vision Artificial Intelligence Theory of Computation Data Mining and Knowledge Discovery Computer and Information Systems Applications |
| ISBN | 3-319-26561-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part IV -- Deep Feature-Action Processing with Mixture of Updates -- Abstract -- 1 Introduction -- 1.1 Actor-Critic and Neural Networks -- 1.2 Deep Learning and RL -- 1.3 Robot Homing -- 2 The Model -- 2.1 Model Architecture and Components -- 2.2 Actor-Critic Combined Network with Double Eligibility Traces -- 2.3 Mixing Gradient with Conjugate Gradient Updates -- 2.4 Deep Blended Actor-Critic Architecture -- 3 Experimental Results -- 3.1 Agent Learning Behavior and Convergence -- References -- Heterogeneous Features Integration via Semi-supervised Multi-modal Deep Networks -- 1 Introduction -- 2 Semi-Supervised Multi-Modal Deep Networks -- 2.1 Model Architecture -- 2.2 Extracting Homogeneous Representations by Root Networks -- 2.3 Feature Fusion with Top Networks -- 3 Experiments -- 3.1 Datasets and Experiment Setup -- 3.2 Experimental Results -- 4 Conclusion -- References -- Multimodal Deep Belief Network Based Link Prediction and User Comment Generation -- 1 Introduction -- 2 Models -- 2.1 Restricted Boltzmann Machine -- 2.2 Deep Belief Network -- 2.3 Multimodal Deep Belief Networks -- 3 Methodology -- 3.1 Link Network Structure Features -- 3.2 User Comment Features -- 3.3 Discriminative Deep Belief Networks -- 3.4 Reconstructive Deep Belief Networks -- 4 Experiments and Analysis -- 4.1 Experiment Setup -- 4.2 Link Prediction Results and Analysis -- 4.3 User Comment Generation Results and Analysis -- 5 Conclusion -- References -- Deep Dropout Artificial Neural Networks for Recognising Digits and Characters in Natural Images -- 1 Introduction -- 2 Methodology -- 2.1 Restricted Boltzmann Machines -- 2.2 Deep Neural Networks -- 2.3 Dropout Method -- 3 Data Set Description -- 4 Application and Results -- 5 Conclusion -- References -- A Multichannel Deep Belief Network for the Classification of EEG Data.
1 Introduction -- 2 Deep Belief Networks -- 3 The Proposed Implementations of Multichannel DBN -- 4 Data Set -- 5 Experimental Results and Discussion -- 6 Conclusion -- References -- Deep Convolutional Neural Networks for Human Activity Recognition with Smartphone Sensors -- Abstract -- 1 Introduction -- 2 Related Works -- 3 Human Activity Recognition with Convolutional Neural Networks -- 3.1 Convolutional Neural Networks -- 3.2 Convolutional Neural Network Architecture and Hyperparameters -- 4 Experiments -- 5 Conclusion -- References -- Concentration Monitoring with High Accuracy but Low Cost EEG Device -- Abstract -- 1 Introduction -- 2 Method -- 2.1 Overall Structure of the Proposed System -- 2.2 Experiment Design -- 2.3 EEG Signal Processing -- 2.4 Candidate Features for Concentration Detection -- 3 Experimental Results -- 4 Conclusion -- Acknowledgements -- References -- Transfer Components Between Subjects for EEG-based Driving Fatigue Detection -- 1 Introduction -- 2 Algorithm Description -- 2.1 Feature Extraction -- 2.2 Transfer Component Analysis -- 3 Experimental Setup -- 3.1 Subjects and Procedure -- 3.2 Data Collection and Pre-processing -- 3.3 Feature Smooth -- 3.4 Feature Extraction -- 3.5 Fatigue Measurement -- 3.6 Detailed Parameters for Training -- 4 Experiment Results -- 5 Conclusion and Future Work -- References -- A Proposed Blind DWT-SVD Watermarking Scheme for EEG Data -- 1 Introduction -- 2 The Proposed EEG Watermarking Approach -- 2.1 EEG Watermarking Embedding -- 2.2 EEG Watermarking Extraction -- 3 Experiments and Results -- 3.1 Dataset -- 3.2 Results -- 4 Conclusion and Future Work -- References -- A Study to Investigate Different EEG Reference Choices in Diagnosing Major Depressive Disorder -- Abstract -- 1 Introduction -- 2 Proposed EEG Measures -- 2.1 Inter-hemispheric Asymmetry -- 2.2 Inter-hemispheric Coherence. 2.3 Power Computation Based on Welch Periodogram Method -- 3 Participant Recruitment and Experiment Design -- 3.1 Study Participants -- 3.2 Experiment Design -- 4 Data Analysis -- 4.1 EEG Data Preprocess -- 4.2 EEG Analysis -- 4.3 Validation -- 5 Results -- 5.1 Calculations of Accuracy, Sensitivity, and Specificity -- 5.2 Low Dimensional Representation -- 5.3 Classification Results -- 6 Conclusions -- References -- Prosthetic Motor Imaginary Task Classification Based on EEG Quality Assessment Features -- 1 Introduction -- 2 Methodology -- 2.1 Signal Recording -- 2.2 Feature Extraction -- 2.3 Classification Model -- 3 Results -- 4 Conclusion and Future Work -- References -- Enhancing Performance of EEG-based Emotion Recognition Systems Using Feature Smoothing -- 1 Introduction -- 2 The EEG-based Emotion Recoginition Model with Feature Smoothing -- 3 Experiments and Results -- 3.1 Dataset -- 3.2 Feature Extraction -- 3.3 Feature Smoothing -- 3.4 Experimental Results -- 4 Conclusion and Future Work -- References -- Intelligent Opinion Mining and Sentiment Analysis Using Artificial Neural Networks -- 1 Introduction -- 2 The State of the Art -- 3 Description of the System -- 4 Conclusions and Perspectives -- References -- Mining Top-k Minimal Redundancy Frequent Patterns over Uncertain Databases -- 1 Introduction -- 2 Preliminaries and Problem Definition -- 3 Proposed Method -- 4 Experimental Results -- 5 Conclusion -- 6 Related Work -- References -- Exploring Social Contagion in Open-Source Communities by Mining Software Repositories -- 1 Introduction -- 2 Related Work and Research Method -- 3 Results and Discussions -- 3.1 Power Law Distribution -- 3.2 Best Time to Start New Projects -- 3.3 Social Contagion in Open-Source Software Development -- 4 Limitations and Future Work -- 5 Conclusion -- References. Data Mining Analysis of an Urban Tunnel Pressure Drop Based on CFD Data -- 1 Introduction -- 2 Methodology -- 3 Experimental Result -- 4 Conclusion -- References -- MapReduce-based Parallelized Approximation of Frequent Itemsets Mining in Uncertain Data -- Abstract -- 1 Introduction -- 2 Related Work -- 3 MapReduce-based Parallel Approximation Algorithm -- 4 Experimental Results -- 4.1 Performance Analysis -- 4.2 Performance Comparisons -- 5 Conclusions -- Acknowledgement -- References -- A MapReduce Based Technique for Mining Behavioral Patterns from Sensor Data -- 1 Introduction -- 2 RFSPs Mining Problem in Wireless Sensor Networks -- 3 RFSPs Mining Using MapReduce Model -- 4 Experimental Results -- 5 Conclusion -- References -- A Methodology for Synthesizing Interdependent Multichannel EEG Data with a Comparison Among Three Blind Source Separation Techniques -- 1 Introduction -- 2 Construction of Synthetic Data -- 3 Evaluation of the Projection Techniques -- 4 Conclusion -- References -- Analysing the Robust EEG Channel Set for Person Authentication -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Dataset -- 3.2 Preprocessing and Feature Extraction -- 3.3 Channel Selection Criteria -- 4 Experimental Details -- 5 Results and Discussion -- 6 Conclusion and Future Work -- References -- Automatic Brain Tumor Segmentation in Multispectral MRI Volumetric Records -- 1 Introduction -- 2 Materials and Methods -- 2.1 BRATS Data Sets -- 2.2 The FCM Cascade -- 2.3 FCM Initialization -- 2.4 Decision Support -- 2.5 Evaluation of Accuracy -- 3 Results and Discussion -- 4 Conclusion -- References -- Real-Time EEG-based Human Emotion Recognition -- Abstract -- 1 Introduction -- 2 Background -- 3 Real-Time Emotion Recognition -- 3.1 Experimental-Design -- 3.2 Emotion Recognition Algorithm -- 4 Comparison and Results -- 5 Software and Tools. 6 Conclusion -- References -- Dynamic 3D Clustering of Spatio-Temporal Brain Data in the NeuCube Spiking Neural Network Architecture on a Case Study of fMRI Data -- 1 Introduction -- 2 The Proposed NeuCube-Based Spiking Neural Network Methodology for Learning, Visualization and Clustering of STBD -- 2.1 Spiking Neural Networks for Modelling STBD -- 2.2 The NeuCube Architecture [3] -- 2.3 3D Dynamic Neuronal Clustering in a NeuCube SNN Model -- 3 Application of the Proposed Method on a Benchmark fMRI STBD -- 3.1 FMRI Data Acquisition Description -- 3.2 FMRI Data Mapping, Learning and Visualization in a SNNc -- 3.3 Dynamic Cluster Evolution in a NeuCube Model on the fMRI Case Study STBD -- 4 Conclusion -- References -- Vigilance Differentiation from EEG Complexity Attributes -- 1 Introduction -- 2 Subjects and Experimental Environment -- 3 Methodology -- 4 Results -- 4.1 Conclusion -- References -- Robust Discriminative Nonnegative Patch Alignment for Occluded Face Recognition -- 1 Introduction -- 2 Robust Discriminative Nonnegative Patch Alignment (RD-NPA) -- 2.1 Part Optimization -- 2.2 Whole Alignment -- 2.3 Objective Function of RD-NPA -- 3 Algorithm for Robust Discriminative Nonnegative Patch Alignment -- 4 Experiments -- 4.1 Data and Parameter Setting -- 4.2 Experimental Results -- 5 Conclusion -- References -- Single-Image Expression Invariant Face Recognition Based on Sparse Representation -- 1 Introduction -- 2 Shape-Constrained Sparse Representation -- 2.1 Shape-Constrained Texture Matching -- 2.2 Feature Interpretation -- 2.3 Sparse Texture Representation (STR) -- 3 Experiments -- 3.1 Shape Change -- 3.2 Expression Impact -- 4 Conclusion -- References -- Intensity-Depth Face Alignment Using Cascade Shape Regression -- 1 Introduction -- 2 Framework -- 2.1 Problem Description -- 2.2 Framework Structure -- 2.3 Feature -- 2.4 Initial Estimation. 3 Experiments. |
| Record Nr. | UNISA-996466217403316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Neural Information Processing : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015, Proceedings, Part II / / edited by Sabri Arik, Tingwen Huang, Weng Kin Lai, Qingshan Liu
| Neural Information Processing : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015, Proceedings, Part II / / edited by Sabri Arik, Tingwen Huang, Weng Kin Lai, Qingshan Liu |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XVI, 666 p. 229 illus.) |
| Disciplina | 006.32 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Pattern recognition systems
Computer vision Artificial intelligence Computer science Data mining Application software Automated Pattern Recognition Computer Vision Artificial Intelligence Theory of Computation Data Mining and Knowledge Discovery Computer and Information Systems Applications |
| ISBN | 3-319-26535-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910484935703321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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