Call for Papers (pdf file)

Scope of the Workshop

The International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM) is the annual workshop organized by the working group Multimedia Understanding through Semantics, Computation and Learning (MUSCLE) of the European Research Consortium for Informatics and Mathematics (ERCIM). This year, IWCIM takes place as a satellite workshop to ICCCI 2020, to be held in Da Nang, Vietnam, on November 30- December 3, 2020.

Multimedia understanding is an essential part of many intelligent applications in our social life, be it in our households, or in commercial, industrial, service, and scientific environments. Analyzing raw data to provide them with semantics is essential to exploit their full potential and help us manage our everyday tasks. Nowadays, raw data usually come from a host of different sensors and other sources, and are different in nature, format, reliability and information content. Multimodal and cross-modal analysis are the only ways to use them at their best. Besides data analysis, this problem is also relevant to data description intended to help storage and mining. Interoperability and exchangeability of heterogeneous and distributed data is a need for any practical application. Semantics is information at the highest level, and inferring it from raw data (that is, from information at the lowest level) entails exploiting both data and prior information to extract structure and meaning.Computation, machine learning, statistical and Bayesian methods are tools to achieve this goal at various levels

The scope of IWCIM 2020 includes, but is not limited to the following topics:

• Multisensor systems
• Multimodal analysis
• Crossmodal data analysis and clustering
• Mixed-reality applications
• Activity and object detection and recognition
• Text and speech recognition
• Multimedia labeling, semantic annotation, and metadata
• Multimodal indexing and searching in very large data-bases
• Big and Linked Data
• Search and mining Big Data
• Large-scale recommendation systems
• Multimedia and Multi-structured data
• Semantic web and Linked Data
• Case studies