Neamat El Gayar – författare

This book constitutes the refereed proceedings of the 10th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2022, held in Dubai, UAE, in November 2022. The conference presents papers on subject such as pattern recognition and machine learning based on artificial neural networks.

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 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.

These proceedings are a record of the Multiple Classi?er Systems Workshop, MCS 2010, held at the Nile University, Egypt in April 2010. Being the ninth in a well-established series of meetings providing an international forum for d- cussion of issues in multiple classi?er system design, the workshop achieved its objective of bringing together researchers from diverse communities (neural n- works, pattern recognition, machine learning and statistics) concerned with this researchtopic.Frommorethan50submissions,theProgramCommitteeselected 31 papers to create an interesting scienti?c program.Paperswere organizedinto sessionsdealingwithclassi?ercombinationandclassi?erselection,diversity,b- ging and boosting, combination of multiple kernels, and applications. The wo- shopprogramandthisvolumewereenrichedbytwoinvitedtalksgivenbyGavin Brown(University of Manchester,UK), and Friedhelm Schwenker(University of Ulm, Germany). As usual, the workshop would not have been possible without the help of many individuals and organizations.First of all, our thanks go to the members of the MCS 2010 Program Committee, whose expertise and dedication helped us create an interesting event that marks the progressmade in this ?eld overthe last year and aspire to chart its future research. The help of James Field from the University of Surrey, who administered the submitted paper reviews, and of Giorgio Fumera who managed the MCS website deserve a particular mention. 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, local organization, and proceedings preparation.

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.