Multimedia Tools and Applications - Call for Papers: Advanced Deep Learning for Computer Vision and Multimedia Applications [1237]
Summary and Scope
Artificial Intelligence (AI) has experienced excellent success in many real-world applications such as gaming, personalized shopping, AI-powered assistants, marketing, healthcare, autonomous systems, etc. So far, Deep Learning (DL) has become widely popular as a subfield of AI in both academia and industry. Due to the broad success of DL, DL has made important contributions in various research and applications such as image classification, image reconstruction, semantic segmentation, object detection, computer aided diagnosis, image-to-image translation, photo-realistic image generation, speech recognition, etc. Although DL has great successes in some applications, it still has some challenges in computer vision and multimedia processing such as pose estimation, person re-identification, human behavior understanding, multimedia quality assessment, computer aided diagnosis, multimedia forensics and security. Furthermore, more existing DL techniques were developed for analyzing natural images. It is worth investigating whether DL techniques can be extensively utilized in deal with different modalities and developing new approaches in different applications.
To provide an open platform for obtaining a variety of discussions and presentations about recent emerging techniques in “Advanced Deep Learning for Computer Vision and Multimedia Applications” is the main goal of this special issue. Related topics include for the special issue but not limited to:
- Image/video processing
- Medical signal processing
- 3D signal processing
- Multimedia quality assessment
- Multimedia forensics and security
- Novel deep learning approaches in the applications of computer vision and multimedia processing
Important Dates:
Open: September 12, 2023
Close: February 28, 2024
Guest Editors
Guo-Shiang Lin - National Chin-Yi University of Technology
Email:gslin@ncut.edu.tw
Jing-Ming Guo - National Taiwan University of Science and Technology
Email: jmguo@mail.ntust.edu.tw
Chia-Hung Yeh - National Taiwan Normal University
Email: chyeh@ntnu.edu.tw
Mianxiong Dong - Muroran Institute of Technology
Email: mx.dong@csse.muroran-it.ac.jp
Submission Guidelines:
Authors should prepare their manuscript according to the Instructions for Authors available from the Multimedia Tools and Applications website (this opens in a new tab). Authors should submit through the online submission site at https://www.editorialmanager.com/mtap/default2.aspx (this opens in a new tab) and select “SI 1237 - Advanced Deep Learning for Computer Vision and Multimedia Applications" when they reach the “Article Type” step in the submission process. Submitted papers should present original, unpublished work, relevant to the topics of the special issue. All submitted papers will be evaluated on the basis of relevance, significance of contribution, technical quality, scholarship, and quality of presentation, by at least three independent reviewers. It is the policy of the journal that no submission, or substantially overlapping submission, be published or be under review at another journal or conference at any time during the review process. Please note that the authors of selected papers presented at IS3C 2023 are invited to submit an extended version of their contributions by taking into consideration both the reviewers’ comments on their conference paper, and the feedback received during presentation at the conference. It is worth clarifying that the extended version is expected to contain a substantial scientific contribution, e.g., in the form of new algorithms, experiments or qualitative/quantitative comparisons, and that neither verbatim transfer of large parts of the conference paper nor reproduction of already published figures will be tolerated. The extended versions of IS3C papers will undergo the standard, rigorous journal review process and be accepted only if well-suited to the topic of this special issue and meeting the scientific level of the journal. Final decisions on all papers are made by the Editor in Chief.