IEEE Symposium on CI in Image, Signal Processing and Synthetic Media (IEEE CISM)

Symposium Chair: Danilo Comminiello - danilo.comminiello[at]uniroma1.it

Technical Activities Liaison/Strategy: Kai Qin

Symposium Technical Chair: Eleonora Grassucci

Symposium Publicity Chair: Valerio Guarrasi

Symposium Industry Chair: Amir Hussain

Symposium Industry Co-Chair: Danilo P. Mandic

Symposium Publication Chair: Beatrice Ombuki-Berman

Scope

We are immersed in a plethora of data in various modalities, such as images, texts, and time-series, which are either produced in the real world - civil surveillance, internet activities and health examination among others or artificially generated data such as synthetic media. Such data contains great value which may power intelligent systems, fuelling unprecedented social and economic benefits. The considerable pace of recent technological advances - gaining insights from past, present and future data in different modalities - has generated considerable benefits to scientific discovery and informed decision-making. Among which, computational intelligence (CI) technology, with deep neural networks as the most well-known representative in this area, features unparalleled powerfulness and flexibility for handling the fast-growing complexity and scalability of scientific and engineering problems.

Compared to traditional approaches which require a deep understanding of the problem and high data quality, CI techniques can learn to solve the problem in a black box manner. Despite uncertain and incomplete data, powerful and adaptive CI techniques can create scalable computational models to solve complex scientific and engineering problems. Particularly, in the fields of computer vision and signal processing, nature and brain inspired techniques have demonstrated remarkable excellence, far outperforming conventional methods in addressing a variety of challenging tasks, from image classification, semantic segmentation, and object detection to speech and language processing, time-series forecasting, and synthetic media generation. Nowadays, more and more new applications related to image, signal processing, and synthetic media keep emerging in different sectors, such as health, space, transportation, education, and entertainment, leading to the surging demands of the theoretical and practical contributions in CI to deal with them.

This symposium aims to bring together researchers and practitioners in academia, industries, and governments to retrospect past achievements, discuss latest studies, and explore future directions about innovating and applying CI techniques, e.g., neural networks, fuzzy systems, and evolutionary computation, to solve open and new problems relevant to image, signal processing, and synthetic media. We welcome submissions about both theoretical developments and practical applications.

Topics of interest include, but are not limited to: