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

Published Cham, Switzerland : Springer, 2018

Click on the following:
Springer Computer Science eBooks
Springer eBooks

Copies

Description 1 online resource (xliii, 824 pages) : illustrations Series Lecture notes in computer science ; 11139 LNCS sublibrary. SL 1, Theoretical computer science and general issues Lecture notes in computer science ; 11139. LNCS sublibrary. SL 1, Theoretical computer science and general issues. 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 I -- Contents -- Part II -- Contents -- Part III -- CNN/Natural Language -- Fast CNN Pruning via Redundancy-Aware Training -- 1 Introduction -- 2 Related Work -- 3 Redundancy-Aware Training -- 3.1 Pruning Weights During Training -- 3.2 Model Partition -- 4 Evaluation 4.1 Compression Result and Time Efficiency -- 4.2 Ablation Study -- 5 Conclusion -- References -- Two-Stream Convolutional Neural Network for Multimodal Matching -- 1 Introduction -- 2 Related Work -- 3 Two-Stream CNN -- 3.1 Network Architecture -- 3.2 Network Learning -- 4 Experiment -- 4.1 Datasets and Evaluation Metrics -- 4.2 Implementation Details -- 4.3 Experimental Results -- 5 Conclusion -- References -- Kernel Graph Convolutional Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Patch Extraction and Normalization -- 3.2 Graph Processing 3.3 Processing New Graphs -- 3.4 Channels -- 4 Experimental Setup -- 4.1 Synthetic Dataset -- 4.2 Real-World Datasets -- 5 Conclusion -- References -- A Histogram of Oriented Gradients for Broken Bars Diagnosis in Squirrel Cage Induction Motors -- Abstract -- 1 Introduction -- 2 Theoretical Background -- 2.1 The Histogram of Oriented Gradients as a Feature Descriptor -- 3 The HOG-MLP Method for Broken Bars Detection -- 4 Experimental Results -- 4.1 Analysis of Parameters for the Proposed Method -- 4.2 Fault Detection Using HOG, MLP and Bayesian Approach -- 5 Conclusions -- Acknowledgments 4.1 Convolutional Neural Network Model -- 4.2 Residual Convolutional Neural Network Model -- 5 Results and Discussion -- 6 Conclusion -- References -- A Convolutional Neural Network Approach for Modeling Semantic Trajectories and Predicting Future Locations -- 1 Introduction -- 2 Related Work -- 3 Theoretical Background -- 3.1 Semantic Trajectories -- 3.2 Convolutional Neural Networks (CNNs) -- 4 CNNs for Semantic Trajectories -- Our Approach -- 5 Evaluation -- 6 Conclusion -- References -- Neural Networks for Multi-lingual Multi-label Document Classification -- 1 Introduction -- 2 Related Work 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 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 Notes International conference proceedings Includes author index Online resource; title from PDF title page (SpringerLink, viewed October 4, 2018) Subject Neural networks (Computer science) -- Congresses 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 proceedings (reports) Conference papers and proceedings Conference papers and proceedings. Actes de congrès. Form Electronic book Author Kůrková, V. (Vera), 1948- editor. Manolopoulos, Yannis, 1957- editor. Hammer, Barbara, 1970- editor. Iliadis, Lazaros S., editor. Maglogiannis, Ilias G., editor. ISBN 9783030014186 3030014185 3030014177 9783030014179 9783030014193 3030014193

  Permalink