Embedded Systems and Software for Deep Learning
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 15 November 2024 | Viewed by 169
Special Issue Editors
Interests: embedded systems and software; low-power technology; embedded deep learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, deep learning has become popular in various applications, including AR/VR, games, computer vision, natural language processing, and so on. Especially, deep learning has been used as a major application for embedded systems such as smartphones and IoT systems. Due to the limited resources in embedded systems, we need to carefully investigate the various constraints in designing and developing deep learning for embedded systems. Among the constraints, performance and memory footprint have been researched abundantly, to the detriment of accuracy. From the aspects of power and energy consumption, there is less research existing in the literature.
The aim of this Special Issue is to excavate new meaningful manuscripts on advanced power- and energy-aware deep learning techniques for embedded systems. The key focus is to present some insights about hardware, compilers, OS, applications, models, etc., in order to achieve high power and energy saving with little performance loss while various deep learning applications run in embedded systems.
In this Special Issue, original research articles and reviews are welcome. Topics may include but are not limited to the following:
- Embedded systems/software/tools for deep learning;
- Optimizations for embedded deep learning;
- Code generation for embedded deep learning;
- Execution engine/OS support for embedded deep learning;
- Low-power and energy technologies for embedded deep learning;
- Deep learning, AR/VR, image processing acceleration techniques for embedded systems.
We look forward to receiving your valuable contributions.
Prof. Dr. Young-Jin Kim
Dr. Hyung-Gyu Lee
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
- embedded systems and software
- edge computing
- embedded deep learning
- hardware–software codesign
