Artificial Neural Networks and Machine Learning -- ICANN 2014 24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15-19, 2014, Proceedings /
Artificial Neural Networks and Machine Learning -- ICANN 2014 24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15-19, 2014, Proceedings / [electronic resource] :
edited by Stefan Wermter, Cornelius Weber, Wlodzislaw Duch, Timo Honkela, Petia Koprinkova-Hristova, Sven Magg, Günther Palm, Allessandro E.P. Villa.
- 1st ed. 2014.
- XXV, 852 p. 338 illus. online resource.
- Theoretical Computer Science and General Issues, 8681 2512-2029 ; .
- Theoretical Computer Science and General Issues, 8681 .
Recurrent Networks -- Sequence Learning -- Echo State Networks -- Recurrent Network Theory -- Competitive Learning and Self-Organisation.- Clustering and Classification -- Trees and Graphs -- Human-Machine Interaction -- Deep Networks.- Theory -- Optimization -- Layered Networks -- Reinforcement Learning and Action -- Vision -- Detection and Recognition -- Invariances and Shape Recovery -- Attention and Pose Estimation -- Supervised Learning -- Ensembles -- Regression -- Classification -- Dynamical Models and Time Series -- Neuroscience -- Cortical Models -- Line Attractors and Neural Fields -- Spiking and Single Cell Models -- Applications -- Users and Social Technologies -- Demonstrations.
The book constitutes the proceedings of the 24th International Conference on Artificial Neural Networks, ICANN 2014, held in Hamburg, Germany, in September 2014. The 107 papers included in the proceedings were carefully reviewed and selected from 173 submissions. The focus of the papers is on following topics: recurrent networks; competitive learning and self-organisation; clustering and classification; trees and graphs; human-machine interaction; deep networks; theory; reinforcement learning and action; vision; supervised learning; dynamical models and time series; neuroscience; and applications.
9783319111797
10.1007/978-3-319-11179-7 doi
Artificial intelligence.
Computer science.
Algorithms.
Pattern recognition systems.
Application software.
Computer vision.
Artificial Intelligence.
Theory of Computation.
Algorithms.
Automated Pattern Recognition.
Computer and Information Systems Applications.
Computer Vision.
Q334-342 TA347.A78
006.3
Recurrent Networks -- Sequence Learning -- Echo State Networks -- Recurrent Network Theory -- Competitive Learning and Self-Organisation.- Clustering and Classification -- Trees and Graphs -- Human-Machine Interaction -- Deep Networks.- Theory -- Optimization -- Layered Networks -- Reinforcement Learning and Action -- Vision -- Detection and Recognition -- Invariances and Shape Recovery -- Attention and Pose Estimation -- Supervised Learning -- Ensembles -- Regression -- Classification -- Dynamical Models and Time Series -- Neuroscience -- Cortical Models -- Line Attractors and Neural Fields -- Spiking and Single Cell Models -- Applications -- Users and Social Technologies -- Demonstrations.
The book constitutes the proceedings of the 24th International Conference on Artificial Neural Networks, ICANN 2014, held in Hamburg, Germany, in September 2014. The 107 papers included in the proceedings were carefully reviewed and selected from 173 submissions. The focus of the papers is on following topics: recurrent networks; competitive learning and self-organisation; clustering and classification; trees and graphs; human-machine interaction; deep networks; theory; reinforcement learning and action; vision; supervised learning; dynamical models and time series; neuroscience; and applications.
9783319111797
10.1007/978-3-319-11179-7 doi
Artificial intelligence.
Computer science.
Algorithms.
Pattern recognition systems.
Application software.
Computer vision.
Artificial Intelligence.
Theory of Computation.
Algorithms.
Automated Pattern Recognition.
Computer and Information Systems Applications.
Computer Vision.
Q334-342 TA347.A78
006.3