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Artificial Neural Networks and Machine Learning – ICANN 2018

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Table of Contents

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    Book Overview
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    Chapter 1 Rank-Revealing Orthogonal Decomposition in Extreme Learning Machine Design
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    Chapter 2 An Improved CAD Framework for Digital Mammogram Classification Using Compound Local Binary Pattern and Chaotic Whale Optimization-Based Kernel Extreme Learning Machine
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    Chapter 3 A Novel Echo State Network Model Using Bayesian Ridge Regression and Independent Component Analysis
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    Chapter 4 A Model for Detection of Angular Velocity of Image Motion Based on the Temporal Tuning of the Drosophila
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    Chapter 5 Local Decimal Pattern for Pollen Image Recognition
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    Chapter 6 New Architecture of Correlated Weights Neural Network for Global Image Transformations
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    Chapter 7 Compression-Based Clustering of Video Human Activity Using an ASCII Encoding
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    Chapter 8 Deep Autoencoders for Additional Insight into Protein Dynamics
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    Chapter 9 Pilot Design of a Rule-Based System and an Artificial Neural Network to Risk Evaluation of Atherosclerotic Plaques in Long-Range Clinical Research
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    Chapter 10 A Multi-channel Multi-classifier Method for Classifying Pancreatic Cystic Neoplasms Based on ResNet
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    Chapter 11 Breast Cancer Histopathological Image Classification via Deep Active Learning and Confidence Boosting
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    Chapter 12 Epileptic Seizure Prediction from EEG Signals Using Unsupervised Learning and a Polling-Based Decision Process
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    Chapter 13 Classification of Bone Tumor on CT Images Using Deep Convolutional Neural Network
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    Chapter 14 DSL: Automatic Liver Segmentation with Faster R-CNN and DeepLab
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    Chapter 15 Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound
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    Chapter 16 An Original Neural Network for Pulmonary Tuberculosis Diagnosis in Radiographs
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    Chapter 17 Computerized Counting-Based System for Acute Lymphoblastic Leukemia Detection in Microscopic Blood Images
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    Chapter 18 Right Ventricle Segmentation in Cardiac MR Images Using U-Net with Partly Dilated Convolution
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    Chapter 19 Model Based on Support Vector Machine for the Estimation of the Heart Rate Variability
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    Chapter 20 High-Resolution Generative Adversarial Neural Networks Applied to Histological Images Generation
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    Chapter 21 Tensor Learning in Multi-view Kernel PCA
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    Chapter 22 ACM: Learning Dynamic Multi-agent Cooperation via Attentional Communication Model
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    Chapter 23 Improving Fuel Economy with LSTM Networks and Reinforcement Learning
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    Chapter 24 Action Markets in Deep Multi-Agent Reinforcement Learning
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    Chapter 25 Continuous-Time Spike-Based Reinforcement Learning for Working Memory Tasks
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    Chapter 26 Reinforcement Learning for Joint Extraction of Entities and Relations
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    Chapter 27 TextNet for Text-Related Image Quality Assessment
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    Chapter 28 A Target Dominant Sets Clustering Algorithm
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    Chapter 29 Input Pattern Complexity Determines Specialist and Generalist Populations in Drosophila Neural Network
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    Chapter 30 A Hybrid Planning Strategy Through Learning from Vision for Target-Directed Navigation
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    Chapter 31 Check Regularization: Combining Modularity and Elasticity for Memory Consolidation
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    Chapter 32 Con-CNAME: A Contextual Multi-armed Bandit Algorithm for Personalized Recommendations
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    Chapter 33 Real-Time Session-Based Recommendations Using LSTM with Neural Embeddings
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    Chapter 34 Imbalanced Data Classification Based on MBCDK-means Undersampling and GA-ANN
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    Chapter 35 Evolutionary Tuning of a Pulse Mormyrid Electromotor Model to Generate Stereotyped Sequences of Electrical Pulse Intervals
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    Chapter 36 An Overview of Frank-Wolfe Optimization for Stochasticity Constrained Interpretable Matrix and Tensor Factorization
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    Chapter 37 A Bio-Feasible Computational Circuit for Neural Activities Persisting and Decaying
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    Chapter 38 Granger Causality to Reveal Functional Connectivity in the Mouse Basal Ganglia-Thalamocortical Circuit
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    Chapter 39 A Temporal Estimate of Integrated Information for Intracranial Functional Connectivity
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    Chapter 40 Randomization vs Optimization in SVM Ensembles
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    Chapter 41 An Energy-Based Convolutional SOM Model with Self-adaptation Capabilities
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    Chapter 42 A Hierarchy Based Influence Maximization Algorithm in Social Networks
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    Chapter 43 Convolutional Neural Networks in Combination with Support Vector Machines for Complex Sequential Data Classification
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    Chapter 44 Classification of SIP Attack Variants with a Hybrid Self-enforcing Network
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    Chapter 45 Generalized Multi-view Unsupervised Feature Selection
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    Chapter 46 Performance Anomaly Detection Models of Virtual Machines for Network Function Virtualization Infrastructure with Machine Learning
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    Chapter 47 Emergence of Sensory Representations Using Prediction in Partially Observable Environments
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    Chapter 48 Change Detection in Individual Users’ Behavior
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    Chapter 49 Extraction and Localization of Non-contaminated Alpha and Gamma Oscillations from EEG Signal Using Finite Impulse Response, Stationary Wavelet Transform, and Custom FIR
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    Chapter 50 Chaotic Complex-Valued Associative Memory with Adaptive Scaling Factor
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    Chapter 51 Computation of Air Traffic Flow Management Performance with Long Short-Term Memories Considering Weather Impact
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    Chapter 52 A Study on the Influence of Wavelet Number Change in the Wavelet Neural Network Architecture for 3D Mesh Deformation Using Trust Region Spherical Parameterization
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    Chapter 53 Combining Memory and Non-linearity in Echo State Networks
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    Chapter 54 A Neural Network of Multiresolution Wavelet Analysis
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    Chapter 55 Fast Supervised Selection of Prototypes for Metric-Based Learning
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    Chapter 56 Modeling Data Center Temperature Profile in Terms of a First Order Polynomial RBF Network Trained by Particle Swarm Optimization
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    Chapter 57 Incorporating Worker Similarity for Label Aggregation in Crowdsourcing
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    Chapter 58 NoSync: Particle Swarm Inspired Distributed DNN Training
Overall attention for this book and its chapters
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1 video uploader


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Artificial Neural Networks and Machine Learning – ICANN 2018
Published by
Springer International Publishing, January 2018
DOI 10.1007/978-3-030-01421-6
978-3-03-001420-9, 978-3-03-001421-6

Věra Kůrková, Yannis Manolopoulos, Barbara Hammer, Lazaros Iliadis, Ilias Maglogiannis

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 19%
Student > Ph. D. Student 5 19%
Student > Master 3 12%
Lecturer 2 8%
Professor 1 4%
Other 1 4%
Unknown 9 35%
Readers by discipline Count As %
Computer Science 10 38%
Engineering 5 19%
Mathematics 1 4%
Arts and Humanities 1 4%
Unknown 9 35%