Explainable Artificial Intelligence for Signal Processing and Recognition
A special issue of Computers (ISSN 2073-431X). This special issue belongs to the section "AI-Driven Innovations".
Deadline for manuscript submissions: 20 May 2026 | Viewed by 116
Special Issue Editor
Interests: machine learning; signal processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid growth of artificial intelligence has transformed the fields of signal processing and pattern recognition, driving advances in biomedical engineering, image analysis, telecommunications, and cognitive radio. However, the increasing complexity of deep learning and other black-box models raises critical challenges regarding transparency, trust, and robustness. To ensure reliable deployment in sensitive domains, there is a pressing need for explainable AI (XAI) methods that not only achieve state-of-the-art performance but also provide interpretable and trustworthy insights into their decision-making processes.
This Special Issue, Explainable Artificial Intelligence for Signal Processing and Recognition, seeks contributions that explore the synergy between XAI, signal processing, and recognition tasks. We are particularly interested in approaches that integrate interpretability into algorithm design, ensuring robustness against noise, variability, and uncertainty inherent in real-world data. Topics include, but are not limited to, explainable models for biomedical signal analysis, interpretable deep learning in medical imaging, transparent frameworks for speech and audio processing, explainability in communication systems, and cognitive radio applications.
We welcome novel methods, methodologies, and applications that advance the frontier of explainable AI in signal processing and recognition, ultimately fostering solutions that are accurate, transparent, and trustworthy for both scientific discovery and practical deployment.
Dr. Andres Alvarez-Meza
Guest Editor
Manuscript Submission Information
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Keywords
- trustworthy AI
- explainable AI (XAI)
- biomedical signal processing
- telecommunication signals
- signal integrity
- ethical AI
- AI security
- image processing
- brain–computer interface
- wireless health monitoring
- deep learning
- machine learning
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