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 2026 takes place as a cross society special session within IEEE ISCAS 2026, to be held in Shangai, China on May 24 - 27, 2026.

Multimedia understanding is an essential part of many intelligent applications in our daily lives, whether in our households or commercial, industrial, service, and scientific environments. Analyzing data acquired from a multitude of multimodal sensors to provide them with semantics is essential to exploit their full potential. Multimodal and cross-modal analyses are the only ways to utilize them at their best. This workshop aims at disseminating original research outcomes in the field of computational intelligence specifically targeted for multimedia understanding. To this end, recent computational approaches, such as deep learning and quantum computing will be explored for various applications, including but not limited to digital twins. The IWCIM Special Session at ISCAS 2026 seeks to function as an interdisciplinary platform that invites researchers from the circuits and systems community to contribute and gain insights from complementary fields, including machine learning, computational intelligence, and multimedia understanding. The scope of IWCIM 2026 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
• Cloud Optimization
• Pervasive intelligence
• Machine learning in multimedia understanding
• Attention based approaches for multimedia understanding
• Diffusion models for multi-modal data analysis
• Multi-modal data analysis in compressed domain
• Multi-modal data analysis for remote sensing applications
• Semantic web and Linked data