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Artificial neural networks and machine learning -- ICANN 2018 : 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings. Part II / Věra Kůrková, Yannis Manolopoulos, Barbara Hammer, Lazaros Iliadis, Ilias Maglogiannis (eds.).

By: (27th : International Conference on Artificial Neural Networks (European Neural Network Society) (27th : 2018 : Rhodes, Greece)Contributor(s): Kůrková, V. (Vera), 1948- [editor.] | Manolopoulos, Yannis, 1957- [editor.] | Hammer, Barbara, 1970- [editor.] | Iliadis, Lazaros S [editor.] | Maglogiannis, Ilias G [editor.]Material type: TextTextSeries: Serienbezeichnung | Lecture notes in computer science ; 11140. | LNCS sublibrary. SL 1, Theoretical computer science and general issues.Publisher: Cham, Switzerland : Springer, 2018Description: 1 online resource (xxviii, 632 pages) : illustrationsContent type: text Media type: computer Carrier type: online resourceISBN: 9783030014216; 3030014215; 9783030014247; 303001424X; 3030014207; 9783030014209; 9783030014223; 3030014223Other title: ICANN 2018Subject(s): Neural networks (Computer science) -- Congresses | 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 | Image processing | Computer networking & communications | Computer security | Algorithms & data structures | Artificial intelligence | Computers -- Computer Graphics | Computers -- Hardware -- General | Computers -- Online Services -- General | Computers -- Security -- General | Computers -- Programming -- Algorithms | Computers -- Intelligence (AI) & Semantics | Neural networks (Computer science)Genre/Form: Electronic books. | Electronic books. | Conference papers and proceedings. Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3/2 LOC classification: QA76.87Online resources: Click here to access online
Contents:
Intro -- Preface -- Organization -- Keynote Talks -- Cognitive Phase Transitions in the Cerebral Cortex -- John Taylor Memorial Lecture -- On the Deep Learning Revolution in Computer Vision -- From Machine Learning to Machine Diagnostics -- Multimodal Deep Learning in Biomedical Image Analysis -- Contents -- Part II -- ELM/Echo State ANN -- Rank-Revealing Orthogonal Decomposition in Extreme Learning Machine Design -- Abstract -- 1 Introduction -- 2 Basic Extreme Learning Machine -- 3 ELM with Rank-Revealing Orthogonal Decomposition -- 4 Modification of Non-contributing Neurons
5 Numerical Examples -- 6 Conclusions -- References -- An Improved CAD Framework for Digital Mammogram Classification Using Compound Local Binary Pattern and Chaotic Whale Optimization-Based Kernel Extreme Learning Machine -- 1 Introduction -- 2 Proposed Methodology -- 2.1 Pre-processing Using CLAHE -- 2.2 Feature Extraction Using Compound Local Binary Pattern (CM-LBP) -- 2.3 Feature Reduction Using PCA -- 2.4 Classification Using CWO-KELM -- 3 Experimental Results and Analysis -- 4 Conclusion -- References
A Novel Echo State Network Model Using Bayesian Ridge Regression and Independent Component Analysis -- 1 Introduction -- 2 Related Work -- 3 Basics of Echo State Network -- 4 Bayesian Ridge Echo State Network (BRESN) -- 4.1 Time Series Reconstruction -- 4.2 Dimensionality Reduction -- 4.3 Bayesian Ridge Regression (BayeRidge) -- 4.4 Hyperparameters Optimization Using Genetic Algorithm -- 5 Results and Discussion -- 5.1 Experimental Setup -- 5.2 Dimensionality Reduction Technique -- 5.3 Accuracy Comparison -- 5.4 Running Time -- 6 Conclusion -- References -- Image Processing
A Model for Detection of Angular Velocity of Image Motion Based on the Temporal Tuning of the Drosophila -- 1 Introduction -- 2 Results -- 3 Methods -- 3.1 Input Signals Simulation -- 3.2 AVDM Neural Layers -- 4 Discussion -- References -- Local Decimal Pattern for Pollen Image Recognition -- Abstract -- 1 Introduction -- 2 Local Decimal Pattern (LDP) -- 3 Pollen Recognition Experiments -- 3.1 Parameter Selection -- 3.2 Experimental Results on Pollenmonitor Dataset -- 3.3 Experimental Comparison and Analysis -- 4 Conclusions -- Acknowledgments -- References
New Architecture of Correlated Weights Neural Network for Global Image Transformations -- Abstract -- 1 Introduction -- 2 Problem Definition -- 3 Network Model -- 4 Learning Method -- 5 Results -- 6 Conclusion -- Acknowledgments -- References -- Compression-Based Clustering of Video Human Activity Using an ASCII Encoding -- 1 Introduction -- 2 Methodology -- 2.1 Normalize Compression Distances -- 2.2 Data Format: From Video to ASCII -- 2.3 Clustering of ASCII Objects Using String Compression -- 3 Experiments and Results -- 4 Conclusions -- References -- Medical/Bioinformatics
Summary: 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.
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International conference proceedings.

Includes author index.

Online resource; title from PDF title page (SpringerLink, viewed October 4, 2018).

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.

Intro -- Preface -- Organization -- Keynote Talks -- Cognitive Phase Transitions in the Cerebral Cortex -- John Taylor Memorial Lecture -- On the Deep Learning Revolution in Computer Vision -- From Machine Learning to Machine Diagnostics -- Multimodal Deep Learning in Biomedical Image Analysis -- Contents -- Part II -- ELM/Echo State ANN -- Rank-Revealing Orthogonal Decomposition in Extreme Learning Machine Design -- Abstract -- 1 Introduction -- 2 Basic Extreme Learning Machine -- 3 ELM with Rank-Revealing Orthogonal Decomposition -- 4 Modification of Non-contributing Neurons

5 Numerical Examples -- 6 Conclusions -- References -- An Improved CAD Framework for Digital Mammogram Classification Using Compound Local Binary Pattern and Chaotic Whale Optimization-Based Kernel Extreme Learning Machine -- 1 Introduction -- 2 Proposed Methodology -- 2.1 Pre-processing Using CLAHE -- 2.2 Feature Extraction Using Compound Local Binary Pattern (CM-LBP) -- 2.3 Feature Reduction Using PCA -- 2.4 Classification Using CWO-KELM -- 3 Experimental Results and Analysis -- 4 Conclusion -- References

A Novel Echo State Network Model Using Bayesian Ridge Regression and Independent Component Analysis -- 1 Introduction -- 2 Related Work -- 3 Basics of Echo State Network -- 4 Bayesian Ridge Echo State Network (BRESN) -- 4.1 Time Series Reconstruction -- 4.2 Dimensionality Reduction -- 4.3 Bayesian Ridge Regression (BayeRidge) -- 4.4 Hyperparameters Optimization Using Genetic Algorithm -- 5 Results and Discussion -- 5.1 Experimental Setup -- 5.2 Dimensionality Reduction Technique -- 5.3 Accuracy Comparison -- 5.4 Running Time -- 6 Conclusion -- References -- Image Processing

A Model for Detection of Angular Velocity of Image Motion Based on the Temporal Tuning of the Drosophila -- 1 Introduction -- 2 Results -- 3 Methods -- 3.1 Input Signals Simulation -- 3.2 AVDM Neural Layers -- 4 Discussion -- References -- Local Decimal Pattern for Pollen Image Recognition -- Abstract -- 1 Introduction -- 2 Local Decimal Pattern (LDP) -- 3 Pollen Recognition Experiments -- 3.1 Parameter Selection -- 3.2 Experimental Results on Pollenmonitor Dataset -- 3.3 Experimental Comparison and Analysis -- 4 Conclusions -- Acknowledgments -- References

New Architecture of Correlated Weights Neural Network for Global Image Transformations -- Abstract -- 1 Introduction -- 2 Problem Definition -- 3 Network Model -- 4 Learning Method -- 5 Results -- 6 Conclusion -- Acknowledgments -- References -- Compression-Based Clustering of Video Human Activity Using an ASCII Encoding -- 1 Introduction -- 2 Methodology -- 2.1 Normalize Compression Distances -- 2.2 Data Format: From Video to ASCII -- 2.3 Clustering of ASCII Objects Using String Compression -- 3 Experiments and Results -- 4 Conclusions -- References -- Medical/Bioinformatics

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