Information Processing in Multimedia Applications

Dear Colleagues,

Multimedia, computer vision, graphics, and machine learning have become ubiquitous in modern information systems, creating new challenges for detection, recognition, indexing, access, search retrieval, automated understanding, and processing, resulting in many applications based on image and signal processing, machine learning, and various multimedia technologies.

Recent advances in pervasive computers, networks, telecommunications, and information technology, along with the proliferation of multimedia mobile devices, have stimulated the rapid development of intelligent applications. These key technologies, using virtual reality, augmented reality, and computational intelligence, are gradually creating a multimedia revolution that will significantly impact a broad spectrum of consumer, business, healthcare, educational, and governmental domains. Advancements in artificial intelligence has resulted in the rapid growth of both machine learning methods and applications in computer vision, image processing, and analysis. The development of parallel computing capabilities in the first decade of the 21st century, which boosted the development of deep neural networks, became a real game-changer in machine vision. This Special Issue covers a range of AI-based theories, methods, algorithms, technologies, and systems for diversified and heterogeneous digital multimedia, imaging, computer graphics, and machine learning areas.

This Special Issue will provide an opportunity for researchers and professionals to discuss the present and future challenges associated with this topic and foster potential collaboration for future progress in these fields. We welcome submissions of original papers concerning all aspects of multimedia, vision, and graphics, ranging from concepts and theoretical developments to advanced technologies and innovative applications. The acceptance and publication of papers will be based on their relevance to the below topics, their clarity of presentation, their originality, and the accuracy of the reported results and proposed solutions.

Topics

Topics of interest are related to the following areas (though this list is not exhaustive):

• Multimedia processing:
  • Audio, image, and video joint processing;
  • Cloud computing and multimedia applications;
  • Multimedia file systems and databases: indexing, recognition and retrieval;
  • Multimedia in internet and web-based systems;
  • Human–computer interactions, interfaces, and multimedia;
  • Distributed multimedia systems;
  • Network and operating system support for multimedia;
  • Machine learning for mobile network architectures;
  • Trends in multimedia information processing;
  • Multimedia ontology and perceptions for multimedia users.
• Machine vision, image processing, and analysis:
  • Image enhancement;
  • Linear and non-linear filtering;
  • Object detection and segmentation;
  • Shape analysis;
  • Scene understanding, analysis, and modeling;
  • Image acquisition;
  • Stereo and multispectral imaging;
  • Embedded vision;
  • Robotic vision;
  • Image modeling and transforming;
  • The modeling of human visual perception;
  • Visual knowledge representation and reasoning.
• Visualization and computer graphics:
  • Computational geometry;
  • Data-driven image synthesis;
  • Graphical data presentation;
  • Computer-aided graphic arts and animation;
  • Virtual and augmented reality;
  • Entertainment, personalized systems, and games.
• Machine learning for multimedia, vision, and graphics:
  • Pattern recognition;
  • Deep neural models;
  • Convolutional networks;
  • Recurrent networks;
  • Graph networks;
  • Generative adversarial networks;
  • Neural-style transfers;
  • Deep reinforcement learning;
  • Big data and multimedia systems;
  • Machine learning and computational intelligence for information retrieval in multimedia systems;
  • Data mining, warehousing, and knowledge extraction.
• Applications:
  • Innovative uses of graphic and vision systems;
  • Image retrieval;
  • Autonomous driving systems;
  • Remote sensing;
  • Digital microscopy;
  • Security and surveyance systems;
  • Document analysis;
  • OCR systems;
  • Medical applications and computational biology;
  • Security in multimedia applications—authentication and watermarking;
  • E-learning, e-commerce, and e-society applications;
  • Intelligent multimedia network applications;
  • Future trends in multimedia systems technologies and applications.

Dr. Marcin Iwanowski
Prof. Dr. Andrzej Śluzek
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. Information is an international peer-reviewed open access monthly 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 1600 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.

• computer vision
• multimedia processing
• machine learning
• deep learning
• image processing