IEEE MULTIMEDIA

Scope & Guideline

Elevating the standards of multimedia scholarship.

Introduction

Welcome to your portal for understanding IEEE MULTIMEDIA, featuring guidelines for its aims and scope. Our guidelines cover trending and emerging topics, identifying the forefront of research. Additionally, we track declining topics, offering insights into areas experiencing reduced scholarly attention. Key highlights include highly cited topics and recently published papers, curated within these guidelines to assist you in navigating influential academic dialogues.
LanguageEnglish
ISSN1070-986x
PublisherIEEE COMPUTER SOC
Support Open AccessNo
CountryUnited States
TypeJournal
Convergefrom 1994 to 2024
AbbreviationIEEE MULTIMEDIA / IEEE Multimedia
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314

Aims and Scopes

The journal 'IEEE MULTIMEDIA' focuses on the intersection of multimedia technology and various applications, emphasizing innovative methodologies, systems, and frameworks that enhance multimedia content generation, processing, and analysis.
  1. Multimodal Data Processing:
    Research in this area involves the integration and analysis of data from multiple modalities, such as audio, video, and text, to improve understanding and usability in various applications, including healthcare and security.
  2. Machine Learning and Deep Learning Applications:
    The journal consistently features works that apply machine learning and deep learning techniques to multimedia problems, such as image recognition, video processing, and emotion detection.
  3. Real-Time Multimedia Systems:
    A significant focus is on the development of systems capable of real-time processing and transmission of multimedia content, addressing challenges like latency, bandwidth, and quality of experience.
  4. Security and Privacy in Multimedia:
    The journal covers advancements in multimedia security, including encryption, watermarking, and privacy-preserving technologies, which are crucial for safeguarding sensitive multimedia data.
  5. Emerging Technologies and Standards:
    Research on emerging multimedia technologies and standards, such as VR, AR, and blockchain applications in media, is a core scope, reflecting the journal's commitment to keeping pace with industry trends.
Recent publications in 'IEEE MULTIMEDIA' reveal emerging themes that reflect the evolving landscape of multimedia research, highlighting innovations and interdisciplinary approaches.
  1. Generative Models and AI in Multimedia:
    An increasing number of papers focus on generative models, particularly Generative Adversarial Networks (GANs), for creating and enhancing multimedia content, which indicates a trend towards AI-driven content generation.
  2. Immersive Technologies:
    Research related to virtual reality (VR) and augmented reality (AR) applications is rapidly growing, reflecting a heightened interest in creating immersive multimedia experiences and their implications in various fields.
  3. Cross-Modal Learning and Interaction:
    There is a significant rise in studies exploring cross-modal learning techniques, where insights from one modality enhance understanding in another, particularly in emotion recognition and multimedia retrieval.
  4. Blockchain for Multimedia Security:
    The application of blockchain technology in multimedia data management and security is emerging as a hot topic, with researchers investigating its potential for enhancing privacy and integrity in multimedia transactions.
  5. Healthcare Applications of Multimedia:
    An increasing trend is observed in the application of multimedia technologies in healthcare, particularly in diagnostics and patient monitoring, driven by the need for innovative solutions in medical imaging and data analysis.

Declining or Waning

While 'IEEE MULTIMEDIA' maintains a robust focus on various multimedia technologies, certain themes have seen a decline in prominence over recent years, indicating shifts in research priorities and interests.
  1. Traditional Multimedia Compression Techniques:
    Research on conventional methods of multimedia compression has decreased as newer, more efficient algorithms and architectures, particularly those leveraging AI and machine learning, gain traction.
  2. Basic Multimedia Content Analysis:
    There is a noticeable decline in studies focusing solely on basic content analysis techniques, as the field has shifted towards more complex, multimodal approaches that incorporate contextual and semantic understanding.
  3. Static Multimedia Interfaces:
    The exploration of static multimedia interfaces, such as basic web-based video players, has waned, giving way to more dynamic and interactive multimedia experiences that utilize immersive technologies.

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