Special Issue on Trustworthy Multi-modal Signal Processing and Applications Submission Date: 2024-12-31 Multi-modal signal processing is a hot and inevitable topic nowadays in many fields such as video processing, medical signal processing as well as intelligent decision systems. It is worth noting that most of today's large models are also driven by multi-modal data, especially visual and text data. Although various methods have been put forward for multi-modal signal processing and gained great success in past decades, it is still challenging to make reliable decisions by using multi-modal data since the quality of different modalities as well as a modality for different samples is hard to be well guaranteed, which leads to untrustworthy predictions or decisions. Therefore, we need to design trustworthy multi-modal signal processing (TMSP) theories and methods.

Manuscript submission information:

There are two major issues that need to be further investigated in TMSP, including data reliability and model reliability. For example, missing or noisy values as well as adversarial examples often exist among multi-modal data, which makes the data unreliable. While the lack of theoretical interpretability hinders the reliability of the model. Therefore, it is an urgent demanding research task to develop trustworthy multi-modal signal processing algorithms for exploring the weaknesses of low-quality multi-modal data and unreliable learning models to enhance the trustworthiness in data processing and intelligent decision systems.

In this special issue, we seek original contributions towards cutting-edge methodologies and applications for trustworthy multi-modal signal processing and attempts to solve the remaining challenges. Researchers and practitioners in both academic and industrial communities are welcomed to share new insights of trustworthy multi-modal signal processing in the field of emerging data processing and intelligent decision systems, such as trustworthy multi-modal signal processing theories and methods, computer-aided medical diagnosis, attack and defense for intelligent decision systems, cybersecurity systems, and unmanned drivingsystems, etc.

Scope of the Special Issue:

Potential contributions may address, but are not limited to, the following topics:

⚫ Trustworthy multi-modal signal processing theories

⚫ Trustworthy multi-modal signal processing models

⚫ Trustworthy multi-modal signal processing with low-quality data

⚫ Uncertainty modeling theories for multi-modal signal processing

⚫ Uncertainty modeling theories for multi-modal data

⚫ Trustworthy multi-modal signal processing for computer vision

⚫ Trustworthy multi-modal signal processing for natural language processing

⚫ Trustworthy multi-modal signal processing social network analysis

⚫ Trustworthy multi-modal signal processing for information retrieval

⚫ Trustworthy multi-modal signal processing for medical data processing

⚫ Trustworthy multi-modal signal processing for cybersecurity systems

⚫ Trustworthy multi-modal signal processing for unmanned driving systems

⚫ Trustworthy multi-modal signal processing for bioinformatics

⚫ Self-supervised trustworthy multi-modal signal processing

⚫ Semi-supervised trustworthy multi-modal signal processing

⚫ Supervised trustworthy multi-modal signal processing

⚫ Unsupervised trustworthy multi-modal signal processing

Important Dates:

Submission Portal Open: May 1st, 2024

Submission Deadline: August 31th, 2024

Acceptance Deadline: December 31st, 2024