Workshop proceedings will be published in the Springer LNAI series.

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Papers are solicited dealing with neural networks, machine learning and pattern recognition which emphasize methodological issues possibly arising in applications.

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Topics:

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Methodological issues

– Supervised learning
– Unsupervised learning
– Combination of supervised and unsupervised learning
– Feedforward, recurrent, and competitive neural nets
– Hierarchical modular architectures and hybrid systems
– Combination of neural networks and Hidden Markov models
– Multiple classifier systems and ensemble methods
– Probabilistic graphical models
– Kernel methods
– Deep architectures

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Applications in Pattern Recognition

– Image processing and segmentation
– Sensor-fusion and multi-modal processing
– Feature extraction, dimension reduction
– Clustering and vector quantization
– Speech and speaker recognition
– Data, text, and web mining
– Bioinformatics/Cheminformatics