Submission Preparation Checklist
As part of the submission process, authors are required to check off their submission's compliance with all of the following items, and submissions may be returned to authors that do not adhere to these guidelines.
- The submission has not been previously published, nor is it before another journal for consideration (or an explanation has been provided in Comments to the Editor).
- The submission file is in PDF format.
- Where available, URLs for the references have been provided.
- The text adheres to the stylistic and bibliographic requirements outlined in the Author Guidelines, which is found in About the Journal.
Special Issue on Embedded Systems for Computer Vision
We are currently witnessing a tremendous surge in the development of smart and autonomous systems. These include autonomous cars, autonomous robots, autonomous drones, and various smart systems in the context of industrial automation. A crucial component in all of these systems is computer vision, where inputs from various sensors such as cameras or lidars are processed and control commands for the desired functionality are generated. Computer vision is also being used for implementing various smart functionality, as well as security, e.g., using facial recognition. These emerging applications of computer vision pose several research challenges. These include the development of high-performance embedded architectures to support computer vision solutions, particularly those based on machine learning, the need for timing guarantees of computer vision algorithms when they are in critical control loops, low-power algorithms and architectures for computer vision, and privacy and security of vision-based applications and systems.
Since 2021, all articles are published under a Creative Commons Attribution 4.0 International license (CC BY 4.0), i.e., the authors retain their copyright (see https://creativecommons.org/licenses/by/4.0/).
Until 2021, all articles were published under a Creative Commons Attribution 3.0 Germany license (CC BY 3.0 DE, see https://creativecommons.org/licenses/by/3.0/de/deed.en).
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- With the exception of the metadata and files of published documents and the documents to be reviewed (currently only in the two journals LITES and Dagstuhl Manifestos), we do not share any of your personal data with third parties.
- We do not track your user behavior or process any of your data for purposes of marketing or advertising.
- There is no automated individual decision-making such as profiling or scoring.
Our web services and log files
Log files of HTTP requests are stored by the web services to guarantee the operation of our services. Log files are deleted regularly, but at the latest after 12 months, and are protected against unauthorized access.
Cookies are only used in our Submission System and the Journal Management System (currently only used for our journal LITES) to manage user sessions. Cookies aren’t required for simply visiting the site and read content.
The Dagstuhl Publishing Services
Dagstuhl Publishing publishes conference proceedings, a journal, and a data journal and consolidates all seminar-related publishing efforts, all in an open access manner. The series can be classified into two groups: (1) service-focused series (OASIcs, LIPIcs, LITES, and DARTS) and (2) seminar-focused series (Dagstuhl Reports, Dagstuhl Manifestos, and Dagstuhl Follow-Ups).
In the service-focused series, peer-reviewed scientific documents and data (in case of DARTS) from all areas of computer science are published. All publications (and their metadata) also contain person-related data provided by authors and editors about themselves for the purpose of identification, such as names, persistent IDs like ORCIDs, affiliations, email addresses, or hyperlinks to academic websites.
The seminar-focused series are strongly intertwined with Dagstuhl’s seminar and workshop program and provide a platform to meet the different requirements from this program regarding documentation and dissemination. These publications also contain person-related data such as names, affiliations, and email addresses of participants.
All bibliographic metadata and documents are published open access, are republished indefinitely and globally accessible on our servers via web pages (http://drops.dagstuhl.de/, http://ojs.dagstuhl.de), data interfaces (“APIs”), and as download. The metadata is available in various machine-readable data formats. You can view all bibliographic metadata and documents stored about you at any time and in full via our Publication Server (DROPS) and the APIs.
Since the document and metadata are processed to fulfill our duties as scientific publisher and only to the extent necessary for the scientific reviewing, publication, documentation, and archival within the different Dagstuhl series and periodicals, there is therefore only a possibility of objection if this arises from your particular situation, and if your fundamental rights and freedoms outweigh the legitimate information interests of the international research community to access the public metadata and documents. If you feel you are in such a situation, please contact our data protection officer via the e-mail address email@example.com. (Please do not use this address for non-privacy related requests. For usual publishing inquiries please contact the publishing team via firstname.lastname@example.org.)
Nevertheless, you are of course free to contact us at any time for the purpose of withdrawing your scientific publications. With the successful withdrawal or retraction of your publication, we will also remove the publication’s person-related data.