Friedhelm Schwenker - Böcker

This book constitutes the refereed post-workshop proceedings of the 5th IAPR TC9 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2018, held in Beijing, China, in August 2018. The 10 revised papers presented in this book focus on pattern recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition and pain intensity estimation, especially the question how to distinguish between human emotions from pain or stress induced by pain is discussed.

This volume consitutes selected papers presented during the First Pan-African Conference on Artificial Intelligence, PanAfriCon AI 2022, held in Addis Ababa, Ethiopia, in October 2022. The 16 papers were thoroughly reviewed and selected from the 49 qualified submissions.

This two-volume set, CCIS 2068 and 2069, constitutes selected papers presented during the Second Pan-African Conference on Artificial Intelligence, PanAfriCon AI 2023, held in Addis Ababa, Ethiopia, in October 2023.

This two-volume set, CCIS 2068 and 2069, constitutes selected papers presented during the Second Pan-African Conference on Artificial Intelligence, PanAfriCon AI 2023, held in Addis Ababa, Ethiopia, in October 2023.

This volume constitutes the proceedings of Third Pan-African Conference on Artificial Intelligence, PanAfriCon AI 2024, held in Addis Ababa, Ethiopia, during October 8–9, 2024.The 15 full papers presented were thoroughly reviewed and selected from 66 submissions. They are organized in the following topical sections: Cyber Security; AI in Medical, Biology & Sociology; Audio and Image Interpretation;  AI in Engineering; and Natural Language Processing, Text and Speech Processing.

This book constitutes the refereed proceedings of the 6th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2014, held in Montreal, QC, Canada, in October 2014.

This book constitutes the thoroughly refereed post-workshop proceedings of the Third IAPR TC3 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2014, held in Stockholm, Sweden, in August 2014, as a satellite event of the International Conference on Pattern Recognition, ICPR 2014. The 14 revised papers presented focus on pattern recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition, user identification, and recognition of human activities.

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 papers address issues in multiple classifier systems and ensemble methods, including pattern recognition, machine learning, neural network, data mining and statistics.

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 Fourth IAPR TC9 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2016, held in Cancun, Mexico, in December 2016.The 13 revised papers presented focus on pattern recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition, user identification, and recognition of human activities.

This book constitutes the refereed proceedings of the 8th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2018, held in Siena, Italy, in September 2018.The 29 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 35 submissions. The papers present and discuss the latest research in all areas of neural network- and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications. Chapter "Bounded Rational Decision-Making with Adaptive Neural Network Priors" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book constitutes the refereed proceedings of the Second IAPR Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2006, held in Ulm, Germany in August/September 2006. The 26 revised papers presented were carefully reviewed and selected from 49 submissions. The papers are organized in topical sections on unsupervised learning, semi-supervised learning, supervised learning, support vector learning, multiple classifier systems, visual object recognition, and data mining in bioinformatics.

TheThirdIAPRTC3WorkshoponArti?cialNeuralNetworksinPatternRec- nition, ANNPR 2008, was held at Pierre and Marie Curie University in Paris (France), July 2-4, 2008. The workshop was organized by the Technical C- mittee on Neural Networks and Computational Intelligence (TC3) that is one of the 20 TCs of the International Association for Pattern Recognition (IAPR). The scope of TC3 includes computational intelligence approaches, such as fuzzy systems, evolutionary computing and arti?cial neural networks and their use in various pattern recognition applications. ANNPR 2008 followed the success of the previous workshops: ANNPR 2003 held at the University of Florence (Italy) andANPPR 2006held at ReisensburgCastle, Universityof Ulm (Germany).All the workshops featured a single-track program including both oral sessions and posters with a focus on active participation from every participant. Inrecentyears,the?eld ofneuralnetworkshasmaturedconsiderablyinboth methodologyandreal-worldapplications.Asre?ectedinthisbook,arti?cialn- ral networks in pattern recognition combine many ideas from machine learning, advanced statistics, signal and image processing for solving complex real-world pattern recognition problems.High quality across such a diverse ?eld of research can only be achieved through a rigorous and selective review process. For this workshop, 57 papers were submitted out of which 29 were selected for inclusion in the proceedings. The oral sessions included 18 papers, while 11 contributions were presented as posters. ANNPR 2008 featured research works in the areas of supervised and unsupervised learning, multiple classi?er systems, pattern recognition in signal and image processing, and feature selection.

The 4th IAPR TC3 Workshop on Arti?cial Neural Networks in Pattern Rec- nition, ANNPR 2010, was held at Nile University (Egypt), April 11-13, 2010. The workshop was organized by the Technical Committee on Neural Networks and Computational Intelligence (TC3) that is one of the 20 technical comm- tees (TC) of the International Association for Pattern Recognition (IAPR). The scope of TC3 includes computational intelligence approaches, such as fuzzy s- tems, evolutionary computing and arti?cial neural networks and their use in various pattern recognition applications. The major topics of ANNPR are supervised and unsupervised learning, f- ture selection, pattern recognition in signal and image processing, and appli- tions in data mining or bioinformatics. High quality across such a diverse ?eld of research is achieved through a rigorous and selective review process. For this workshop, 42 papers were submitted and 23 of them were selected for inc- sion in the proceedings. The workshop was enriched by three invited talks given by Barbara Hammer, University of Bielefeld, Germany, Amir F. Atiya, Cairo University, Egypt, and Mohamed Kamel, University of Waterloo, Canada.We would like to thank all authors for the e?ort they put into their subm- sions, and the Scienti?c Committee for taking the time to provide high-quality reviews and selecting the best contributions for the ?nal workshop program. Special thanks are due to the members of the Nile University Organizing C- mittee,AhmedSalah,AmiraElBaroudy,EsraaAly,HebaEzzat,NesrineSameh, Rana Salah and Mohamed Zahhar for their indispensable contributions to the registration management and local organization.

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.

This book constitutes the refereed proceedings of the 5th INNS IAPR TC3 GIRPR International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2012, held in Trento, Italy, in September 2012. The 21 revised full papers presented were carefully reviewed and selected for inclusion in this volume. They cover a large range of topics in the field of neural network- and machine learning-based pattern recognition presenting and discussing the latest research, results, and ideas in these areas.

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.