Journal Information
Information Fusion
Impact Factor:

Call For Papers
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.
Last updated by Dou Sun in 2017-09-23
Special Issues
Special Issue on Information Fusion for Emotion-aware Intelligent Systems
Submission Date: 2018-02-15

In the past decade, computer and information industry has experienced rapid changes in both plat-form scale and scope of applications. Computers, smart phones, clouds, social networks, and super-computers demand not only high performance but also high degree of machine intelligence. In fact, we are entering an era of big data and cognitive computing. This trendy movement is observed by the pervasive use of mobile phones, storage and computing clouds, revival of artificial intelligence in practice, extended supercomputer applications, and wide spread deployment of Internet of Things (IoT) platforms. While the rapidly developed technology benefits people’s material life in many aspects, people begin to concern about human spiritual life and focus on how can information fusion technologies facilitate emotion-aware healthcare data acquisition, representation, and analy-sis. It is envisioned that IoT, clouds, big data and cognitive learning will be the success factors for realizing emotion-aware intelligent systems, leading effective emotion care and smart mental healthcare solutions. In this relatively new area, emotional information from multiple sources are combined to improve system’s intelligence or obtain useful information. For example, combining audio and video data to make machine smarter, or to obtain joint feature representation. This special issue focuses on sharing recent advances in algorithms and applications about emotion-aware intelligent systems. Topics appropriate for this special issue include novel supervised, unsu-pervised, semi-supervised and reinforcement algorithms, new architectures, and applications related to emotion-aware intelligent systems and information fusion. Topics appropriate for this special issue include (but are not necessarily limited to): - New models for emotion-aware intelligent systems - Deep learning models for emotional data processing - Feature fusion for emotion-aware intelligent systems - Shared emotional representation learning - Improved algorithms for emotion-aware intelligent systems - Combining multiple models for emotion-aware intelligent systems - Analysis on big emotional data - Emotion-aware intelligent systems for information fusion - Hierarchical emotion-aware intelligent systems for information fusion - Emotion-control healthcare applications such as mental healthcare systems, emotion-control by robotics technology and emotion interaction through IoT and clouds - Emotion-aware intelligent applications in computer vision related areas such as emotion recognition and so on - Emotion-aware intelligent applications in audio areas such as recognize emotion from one’s voice, generate emotional voice and so on
Last updated by Dou Sun in 2017-09-23
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