Friedhelm Schwenker Knihy

This book constitutes the refereed proceedings of the 12th International Workshop on Multiple Classifier Systems, MCS 2015, held in Günzburg, Germany, in June/July 2015. The 19 revised papers presented were carefully reviewed and selected from 25 submissions. The papers address issues in multiple classifier systems and ensemble methods, including pattern recognition, machine learning, neural network, data mining and statistics. They are organized in topical sections on theory and algorithms and application and evaluation.

This book constitutes the refereed proceedings of the 7th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2016, held in Ulm, Germany, in September 2016.

This book constitutes the thoroughly refereed post-workshop proceedings of the First IAPR TC3 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction (MPRSS2012), held in Tsukuba, Japan in November 2012, in collaboration with the NLGD Festival of Games. The 21 revised papers presented during the workshop cover topics on facial expression recognition, audiovisual emotion recognition, multimodal Information fusion architectures, learning from unlabeled and partially labeled data, learning of time series, companion technologies and robotics.

This book constitutes thoroughly refereed revised selected papers from the First IAPR TC3 Workshop on Partially Supervised Learning, PSL 2011, held in Ulm, Germany, in September 2011. The 14 papers presented in this volume were carefully reviewed and selected for inclusion in the book, which also includes 3 invited talks. PSL 2011 dealt with methodological issues as well as real-world applications of PSL. The main methodological issues were: combination of supervised and unsupervised learning; diffusion learning; semi-supervised classification, regression, and clustering; learning with deep architectures; active learning; PSL with vague, fuzzy, or uncertain teaching signals; learning, or statistical pattern recognition; and PSL in cognitive systems. Applications of PSL included: image and signal processing; multi-modal information processing; sensor/information fusion; human computer interaction; data mining and Web mining; forensic anthropology; and bioinformatics.

The book covers a range of topics in machine learning, focusing on both unsupervised and supervised learning techniques. It begins with unsupervised learning methods, including effective nonparametric estimation of probability density functions and comparisons of spatio-temporal organization maps for speech recognition. It also discusses adaptive feedback inhibition to enhance pattern discrimination and various semi-supervised learning strategies. In the realm of supervised learning, the text explores training radial basis functions via gradient descent and presents a local tangent space alignment-based transductive classification algorithm. It highlights incremental manifold learning and introduces a convolutional neural network designed to tolerate synaptic faults, particularly for low-power analog hardware applications. Support vector learning is addressed through regression using Mahalanobis kernels and incremental training methods for support vector machines. The book also examines multiple classifier systems, including their application in embedded string patterns and facial feature localization using multiple neural networks. Visual object recognition is another key focus, detailing object detection with sparse convolutional neural networks and image classification through geometric appearance learning. Additionally, it touches on eye detection systems and data mining in bioinformatics, including feature reduction m