Click here to download the call for special sessions.

As additional special sessions are announced, the title of each confirmed special session will be added to the topic list above in the paper submission interface. Authors submitting to a special session need to delay their submission until the special sessions are available.

• SS1 Intelligent Information Fusion
• SS2 Dynamic Data Driven Application Systems for Sensor Data Problems
• SS3 Context-based Information Fusion

Description: Research on Intelligent Systems for information fusion has matured during the last years and many effective applications of this technology are now deployed. The problem of Information Fusion has attracted significant attention in the artificial intelligence and machine learning community, trying to innovate in the techniques used for combining the data and to provide new models for estimations and predictions. The growing advances of Information Fusion accompanied with the advances of sensor technologies and distributed computing systems has led to new applications in different environments such as remote sensing, distributed surveillance, smart home care, network management etc. With the continuing expansion of the domain of interest and the increasing complexity of the collected information, intelligent techniques for fusion processing have become a crucial component in information fusion applications. In this sense, Intelligent systems can improve high level information fusion aimed at supporting decision making and/or intelligent information management.

Organizers: Juan Manuel Corchado, Javier Bajo, Tiancheng Li

Description: The Dynamic Data-Driven Application Systems (DDDAS) paradigm shapes a symbiotic feedback ecosystem consisting of models of physical and engineered systems and application instrumentation. Precisely, DDDAS establishes new avenues for accurate analysis and robust prediction, and control in application systems using multi-modal fusion of sensory data. The ubiquitous Big Data problems place the DDDAS as a unifying framework among applications, mathematical and statistical modeling, as well as information systems. Such challenges make the DDDAS paradigm now more relevant than ever that integrate modeling, measurements, and software. The DDDAS Session invites papers that demonstrate advances in the DDDAS paradigm that combine real-world applications, contemporary mathematical approaches, real-time large scale measurements, with software solutions. Key applications requiring DDDAS high-end computing solutions include distributed wireless platforms, distributed processing, collection and processing of sensor data for situation awareness, and critical infrastructure systems.

Organizers: Erik Blasch, Frederica Darema, Vasileios Maroulas, Ioannis D. Schizas

Description: The goal of the proposed session is discussing approaches to context-based information fusion. It will cover the design and development of information fusion solutions integrating sensory data with contextual knowledge. The context may be spread at different levels, with static or dynamic structure, and be represented in different ways, as maps, knowledge-bases, ontologies, etc. It can constitute a powerful tool to favour adaptability and systém performance. Therefore, the session covers both representation and exploitation mechanisms so that this knowledge can be efficiently integrated in the fusion process and enable adaptation mechanisms under different possible paradigms (intelligent systems, knowledge management, integration in fusion algorithms, etc). The applicability of advanced approaches can be illustrated with real-world applications of information fusion requiring a ontextualized approach.

Organizers: Jesus Garcia, Lauro Snidaro, José M. Molina, Ingrid Visentini