The journal is intended to present within a single forum all of the developments in the field of multi-sensor, multi-source information fusion and thereby promote the synergism among the many disciplines that are contributing to its growth. The journal is the premier vehicle for disseminating information on all aspects of research and development in the field of information fusion. Articles are expected to emphasize one or more of the three facets: architectures, algorithms, and applications. Papers dealing with fundamental theoretical analyses as well as those demonstrating their application to real-world problems will be welcome. The journal publishes original papers, letters to the Editors and from time to time invited review articles, in all areas related to the information fusion arena including, but not limited to, the following suggested topics:

• Data/Image, Feature, Decision, and Multilevel Fusion
• Multi-classifier/Decision Systems
• Multi-Look Temporal Fusion
• Multi-Sensor, Multi-Source Fusion System Architectures
• Distributed and Wireless Sensor Networks
• Higher Level Fusion Topics Including Situation Awareness And Management
• Multi-Sensor Management and Real-Time Applications
• Adaptive And Self-Improving Fusion System Architectures
• Active, Passive, And Mixed Sensor Suites
• Multi-Sensor And Distributed Sensor System Design
• Fusion Learning In Imperfect, Imprecise And Incomplete Environments
• Intelligent Techniques For Fusion Processing
• Fusion System Design And Algorithmic Issues
• Fusion System Computational Resources and Demands Optimization
• Special Purpose Hardware Dedicated To Fusion Applications
• Mining Remotely Sensed Multi-Spectral/Hyper-Spectral Image Data Bases
• Information Fusion Applications in Intrusion Detection, Network Security, Information Security and Assurance arena
• Applications such as Robotics, Space, Bio-medical, Transportation, Economics, and Financial Information Systems
• Real-World Issues such as Computational Demands, Real-Time Constraints in the context of Fusion systems.

Special Issue on Multimodal Fusion Technologies to counter Disinformation
Submission Date: 2023-06-30

Disinformation, understood as any kind of misleading, false, or incorrect information that are intentionally spread, is currently an increasingly complex challenge to society and everyday life in most of our current activities. Due to the global and widespread use of online social network (OSN) platforms and messaging services, any user may generate new content and distribute it easily to thousands (even millions) of users in seconds. Progressively, text is giving way to new forms of multimodal content, involving audio, image and video. This has had a major impact in the analysis of this content with traditional computational methods. The vast amount of data, combined with the new multimodality dimension, the number of people connected, and the underlying dynamics in the spreading and consumption of this toxic information by people, makes the processing and the detection of disinformation a challenge never seen before, evidencing the need for new approaches and technologies.

The problem of disinformation detection in OSN can be studied from a multimodal (textual and multimedia), multitarget (if we focus on the uses or actors who spread the misinformation, which can be humans or bots), multilayer (when focus on the sources, their interconnections and how are combined), multilingual (when several languages are considered and handled), or multidisciplinary (if we consider the background from behavioral science to identify patterns or actors who create and disseminate misinformation) perspective. Even if it is only considered from a computational perspective, the number of research areas involved in this problem is very large, from Natural Language Processing, Machine Learning (Classification, Deep Learning, Clustering), Image and Video processing, Multimedia technology, Social Network Analysis, Complex Networks, Graph Knowledge, to Cibersecurity or cybercrime, just to mention a few.
This special issue is devoted to the revision of current and promising new methods, algorithms and technologies that can be used to help tackling the problem of disinformation.

Topics of Interest:

• Dis- and Misinformation / Opinion / Knowledge spread and modelling
• Methods and techniques for the generation and identification of fabricated and manipulated content (e.g. deep fakes, fake news, fake audios, fake videos)
• Data knowledge extraction (scrapping) for disinformation
• Technologies for extremism, polarization, and radicalization detection and prevention (e.g. political, religious)
• AI-supported fact checking and detection of disinformation campaigns
• Cybercrime: crime detection and investigation methods and techniques for disinformation
• Real – world case studies and tools against disinformation and misinformation
• Multimodal fusion methods for disinformation detection and analysis
• Multimodal approaches for profiling disinformation spreaders
• Detection and prevention of multimodal content spreading disinformation
• Detection of fake content and disinformation in Online Social Networks
• Multimedia methods for disinformation detection and analysis
• NLP methods for disinformation detection and analysis
• Machine Learning (e.g. Deep Learning) methods for disinformation detection and analysis
• Multimodal detection of conspiracy theories

Important Dates:
Submission Portal Open: January 15th, 2023
Submission Deadline: June 30th, 2023
Acceptance Deadline: December 15th, 2023 

Special Issue on New Trends in Information Fusion and Decision Making: Social Networks and Opinion Dynamics
Submission Date: 2023-11-30

In decision making, the opinions of managers, possibly from different organizations or from different areas of the same organization and, therefore, with distinct skills and varied knowledge, are fused to achieve a common solution. With the rapid development of information and communication technology and the appearance of new decision-making paradigms, especially social networks, Web 2.0 and e-democracy, have modified the environment in which group decision making happens. Indeed, the internet and/or smart devices provide people with more opportunities of expressing and using their preferences when interacting with other people, the decision making environment to be dynamic and heterogeneous. Social networks and opinion dynamics provide potent tools for modelling both the fusion of information fusion and the decision making process itself, and as such they have attracted wide interest from scholars of different fields, including computer science and engineering, physics, politics and management sciences.

The aim of this special issue is to encourage active researchers to report their latest and best results regarding information fusion and decision making by integrating social networks and opinion dynamics.

Important Dates:
Submission Portal Open: January 31st, 2023
Submission Deadline: November 30th, 2023
Acceptance Deadline: March 31st, 2024