Call for Papers: Real-time 2D/3D Image Processing with Deep Learning [1171]

Brief description/scope

Recently, deep learning techniques are getting essential components for 2D/3D image processing related researches. A highly flexible deep learning has emerged as a disruptive technology to enhance the performance of existing machine learning techniques and to solve previously intractable problems. 2D/3D image process has been identified as one of the key research fields where deep learning can contribute significantly. Vehicles with sensors or medical data have latency constraints, the real-time processing of 2D and 3D images acquired from depth sensors or medical equipment is a key issue to be addressed in research and industrial fields. These aspects include algorithmic computational complexity, hardware implementation, and software optimization for the purpose of making 2D/3D image processing system to operate in real-time using deep learning for an application of interest.

Deep learning for 2D/3D image processing is a relatively new theme and real-time 2D/3D image processing based deep learning method can be efficiently performed by using convolutional neural networks. This special issue address the real-time aspects of 2D/3D image processing and aspects of deep learning solutions in various imaging systems and applications to support decision or to provide meaningful and critical information. Thus this special issue propose various deep learning models for a variety of applications, ranging from 2D to 3D image analysis.

Deep learning related technologies are at the core of the current fourth industrial revolution and these deep learning techniques have a big impact on the automatic understanding and analysis of images. The convergence of large-scale annotated image datasets and affordable GPU hardware has allowed the training of neural networks for image data analysis tasks which were previously addressed with hand-crafted features.

The papers should not be submitted simultaneously for publication elsewhere. Submissions of high quality papers describing future potentials or on-going work are invited.

Topics of interest include, but are not limited to:

  • Signal, image and video real-time processing algorithm in deep learning
  • Real-time acquisition and processing of depth sensing camera in deep learning
  • Real-time face reconstruction from depth sensing camera
  • Real-time 3D imaging processing in deep learning
  • 3D Reconstruction in depth sensing Camera
  • Real-time MRI and X-ray image reconstruction in deep learning
  • Non-Visible imaging processing in depth sensing camera
  • Deep learning models for real-time computational methods
  • Real-time super-resolution image processing in deep learning
  • Face and gesture recognition and authentication
  • Biometrics and biomedical image analysis
  • Action recognition
  • 3D reconstruction from Multiview and multi sensors

Guest editors

Prof Soo Kyun Kim (Lead Guest Editor)
Pai Chai University, South Korea, Email: kimsk@pcu.kr
Prof Min-Hyung Choi, University of Colorado at Denver, USA, Email: Min.Choi@ucdenver.edu
Prof Junchul Chun, Kyonggi University, South Korea, Email: jcchun@kgu.ac.kr
Prof Xibin Jia, Beijing University of Technology, China, Email : jiaxibin@bjut.edu.cn

Important Dates/Tentative schedule

Submission deadline:            extended to 29 June 2020
Final Manuscript due:           30 October 2020
Tentative publication date:   31 December 2020

Submission Guidelines

Authors should prepare their manuscript according to the Instructions for Authors available from the Multimedia Tools and Applications website. Authors should submit through the online submission site at https://www.editorialmanager.com/mtap/default.aspx and select “1171 - Real-time 2D/3D Image Processing with Deep Learning” when they reach the “Article Type” step in the submission process. Submitted papers should present original, unpublished work, relevant to one of 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