Recent Advances in Deep Learning in Human-Machine Interaction
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 15 July 2025 | Viewed by 842
Special Issue Editors
Interests: mobile computing; mobile sensing; AIoT; cyber security; wearable; biometric; authentication; human computer integration
Interests: mobile computing; AIoT; IoT; cloud computing; edge computing; deep learning; computer vision; human computer integration
Special Issue Information
Dear Colleagues,
We are pleased to invite you to contribute to this Special Issue of Electronics entitled “Recent Advances in Deep Learning in Human–Machine Interaction.”
As a subset of artificial intelligence, deep learning has significantly transformed the landscape of human–machine interaction (HMI), enabling more intuitive and effective interactions to take place. This Special Issue aims to explore cutting-edge developments in deep learning that enhance, optimize, and redefine these interactions. The focus of this issue will be on how these advanced models and techniques can more accurately interpret human gestures, emotions, and commands, leading to more natural and seamless user experiences.
Deep learning in human–machine interaction is rapidly evolving, opening new avenues for research on these technologies and their applications across the healthcare, automotive, entertainment, and education sectors. We seek original research and review articles that not only discuss the theoretical advancements but also demonstrate the practical implementations and societal impacts of these technologies.
Topics of interest for this Special Issue include, but are not limited to, the following:
- Deep learning models for gesture recognition;
- Deep learning models for emotion recognition;
- Enhancements in conversational agents and virtual assistants;
- Adaptive user interfaces based on user behavior and preferences;
- Biometric systems for secure and personalized HMI;
- Applications of deep learning in assistive technologies;
- Deep learning in augmented and virtual reality interfaces;
- Neural interfaces and brain–computer interaction;
- Security and privacy challenges in HMI;
- Ethical considerations and challenges in AI-driven HMI;
- Real-time processing and decision-making systems for dynamic HMI.
We look forward to receiving your contributions.
Dr. Zi Wang
Dr. Sen He
Dr. Wei Zhang
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- deep learning
- human–machine interaction
- gesture recognition
- emotion recognition
- conversational agents
- adaptive interfaces
- biometric systems
- augmented reality
- virtual reality
- neural interfaces
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