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Pattern recognition is an essential aspect of learning and behaviour analysis for all living things. It may include different natural actions in real-life scenarios, such as recognition of spoken words and languages, discrimination of human traits and fingerprints, visual identification of objects, and capturing the interaction mechanisms among different individuals. Patterns can be found everywhere in multiple contexts, including biology, medicine and healthcare, text and document analysis, image processing and information retrieval. They can assume multiple aspects, including groups of documents characterised by the same language or script, image regions with uniform characteristics, and social communities in complex networks. In recent time, the complex natural phenomena characterising most of the real-life scenarios have required more specialised methods to be introduced for the extraction and recognition of different types of patterns. In particular, machine learning, intelligent systems and statistical analysis are playing a role of prior importance in the extraction, analysis and identification of patterns in different real-life scenarios.

In this context, the main goal of this workshop is presenting the advancement of the state-of-the-art in statistical and data mining tools, as well as the introduction of innovative and intelligent systems for pattern extraction, analysis and recognition aiming to solve real life problems.

• Pattern recognition in multimedia data, including images, sounds, or videos
• Pattern recognition for document analysis
• Machine learning methods for text mining
• Statistical methods for pattern extraction in language processing
• Pattern identification and classification in chemical and physical data
• Intelligent systems for classification of sensor data
• Machine learning and statistical methods in healthcare and medical scenarios
• Intelligent systems for cyber security
• Pattern recognition in complex networks
• Pattern extraction in bioinformatics and computational biology
• Industrial applications of pattern recognition
• Deep learning for pattern extraction in image processing
• Machine learning methods for speech recognition
• Statistical methods for pattern extraction on the web
• Intelligent systems for big data analysis
• Machine learning methods for pattern extraction from aerospace data
• Classification methods for remotely sensed images

Please consider to send your contribution to:

1st Workshop on Machine Learning, Intelligent Systems and Statistical Analysis for Pattern Recognition in Real-life Scenarios (ML-ISAPR 2018) that will happen in the 9th International Conference on Information Intelligence Systems Applications (IISA 2018) on 23 July 2018 in Zakynthos, Greece.

The main goal of the workshop is presenting the advancement of the state-of-the-art in statistical and data mining tools, as well as the introduction of innovative and intelligent systems for pattern extraction, analysis and recognition aiming to solve real life problems.

Topics to be discussed (but not limited to):

• Pattern recognition in multimedia data, including images, sound and videos
• Pattern recognition for document analysis
• Machine learning methods for text mining
• Statistical methods for pattern extraction in language processing
• Pattern identification and classification in chemical and physical data
• Intelligent systems for classification of sensor data
• Machine learning and statistical methods in healthcare and medical scenarios
• Intelligent systems for cyber security
• Pattern recognition in complex networks
• Pattern extraction in bioinformatics and computational biology
• Industrial applications of pattern recognition
• Deep learning for pattern extraction in image processing
• Machine learning methods for speech recognition
• Statistical methods for pattern extraction on the web
• Intelligent systems for big data analysis
• Machine learning methods for pattern extraction from aerospace data
• Classification methods for remotely sensed images

Conference proceedings will be published in IEEE Xplore Digital Library.

Chairs:

Alessia Amelio, DIMES University of Calabria, Italy

Carlos A.B. Mello, Center of Informatics, Federal University of Pernambuco, Brazil

Radmila Janković, Mathematical Institute of the Serbian Academy of Sciences and Arts, Serbia

Important Dates:

Paper Submission: May 20, 2018

Author Notification: June 5 , 2018

Camera-Ready: June 15, 2018

For more information:

aamelio@dimes.unical.it, cabm@cin.ufpe.br, rjankovic@mi.sanu.ac.rs

We are waiting for your contribution!

Paper Submission: June 04 , 2018

Author Notification: June 15 , 2018

Camera-Ready: June 15, 2018

Alessia Amelio

DIMES University of Calabria

Via Pietro Bucci, 87036 Rende (CS), Italy

email: aamelio@dimes.unical.it

Carlos A.B. Mello,

Center of Informatics, Federal University of Pernambuco (CIn/UFPE)

Cidade Universitária – Recife – Brazil

50740-560

email: cabm@cin.ufpe.br

Radmila Janković

Mathematical Institute of the Serbian Academy of Sciences and Arts

Kneza Mihaila 56, Belgrade 11000, Serbia

email: rjankovic@mi.sanu.ac.rs

Abdolrahman Peimankar, Technical University of Denmak, Denmark

Andrea Tagarelli, DIMES University of Calabria, Italy

Ángel Sanchez, Rey Juan Carlos University, Spain

Arti Saxena, Manav Rachna International University, India

Gufran Ahmad Ansari, Qassim University, Kingdom of Saudi Arabia

Hasan Al-Marzouqi, Petroleum Institute, United Arab Emirates

Jelena Velimirovic, Mathematical Institute of the Serbian Academy of Sciences and Arts, Serbia

Lazar Velimirovic, Mathematical Institute of the Serbian Academy of Sciences and Arts, Serbia

Michele Ianni, DIMES University of Calabria, Italy

Rafael Galvão de Mesquita, Federal Univeristy of Pernambuco, Brazil

Sadaqat Ur Rehman, Tsinghua University, China

Tsang Ing Ren, Federal University of Pernambuco, Brazil

Vinh Truong Hoang, Ho Chi Minh City Open University, Vietnam

Zeljko Dzunic, The University of Nis Information System (JUNIS), Serbia

Ivo Draganov, New Bulgarian University, Bulgaria

Roberto Interdonato, CIRAD UMR TETIS, France

Katerina Kabassi, Technological Educational Institute of Ionian Islands, Greece

Zulfiqar Ali, The University of Lahore, Pakistan

Andreas Kanavos, University of Patras, Greece

Ioannis Hatzilygeroudis, University of Patras, Greece

Sadiq Hussain, Dibrugarh University, India

Submitted papers should include original work not previously published or being under consideration in any journal, conference or other workshop.

Papers should be submitted as a PDF file and follow the IEEE conference format, according to the general Instructions for Authors of IISA 2018 (see the IISA 2018 “Instructions for Authors” page for appropriate templates in both Latex and MS Word). Papers for ML-ISAPR 2018 should be submitted through the general IISA2018 paper submission system (EasyChair).

Accepted papers will be published in the IEEE Proceedings of IISA2018 and will be included in the IEEE Xplore Digital Library (IEL, http://ieeexplore.ieee.org).