About the Journal

International Machine Learning Journal and Computer Engineering (IMLJCE)

9808:675X

Highly Cited Journal

Acceptance Ration below: 8%

The International Machine Learning Journal and Computer Engineering (IMLJCE) is a prestigious and forward-thinking scholarly publication that transcends the boundaries of machine learning (ML) and computer engineering. IMLJCE serves as a dynamic platform for researchers, engineers, and innovators to explore the rich interplay between ML and computer engineering, fostering interdisciplinary collaboration and technological advancement.

IMLJCE's mission is to facilitate excellence in both machine learning and computer engineering by providing a global platform for knowledge exchange, interdisciplinary discourse, and innovation. Our core objectives include:

  1. Advancing ML and Computer Engineering: Promoting pioneering research that propels the frontiers of AI and computer engineering, driving technological progress.

  2. Knowledge Dissemination: Facilitating the dissemination of knowledge, best practices, and emerging trends at the intersection of ML and computer engineering.

  3. Interdisciplinary Collaboration: Encouraging collaboration across disciplines, recognizing the pivotal role of ML and computer engineering in shaping the digital future.

  4. Ethical and Responsible Technology: Emphasizing research integrity and the ethical development and deployment of technology for societal benefit.

IMLJCE welcomes contributions that span a diverse spectrum of topics within the domains of machine learning and computer engineering. Our primary focus areas include, but are not limited to:

  1. Machine Learning in Computer Engineering:

    • ML-driven hardware and software optimization
    • ML-based design automation
    • ML applications in computer architecture

  2. Computer Vision and Image Processing:

    • Computer vision algorithms and applications
    • Image and video analysis
    • Object recognition and tracking

  3. Data-Intensive Computing:

    • Big data analytics and processing
    • ML algorithms for large-scale data
    • Data-driven decision-making in computer engineering

  4. Ethical Technology and Responsible Engineering:

    • AI ethics and bias mitigation
    • AI transparency and fairness
    • Ethical considerations in computer engineering

IMLJCE offers a versatile platform for scholarly contributions, including:

  • Research Papers: Original research articles presenting innovative findings, methodologies, and insights.
  • Review Articles: Comprehensive surveys of current research trends and developments in ML and computer engineering.
  • Technical Notes: Concise reports on novel techniques, tools, or experimental results.
  • Case Studies: In-depth examinations of real-world applications and their impact on technology and engineering.
  • Editorials: Thoughtful reflections on emerging issues, trends, and challenges at the intersection of ML and computer engineering.

The International Machine Learning Journal and Computer Engineering (IMLJCE) is designed to cater to a diverse and global audience, including:

  • Researchers and Practitioners: Eager to share their research, collaborate, and stay updated on the latest advancements in ML and computer engineering.
  • Academics and Educators: Seeking authoritative resources to support teaching and learning in these interdisciplinary domains.
  • Industry Professionals: Leveraging ML and computer engineering to drive innovation, efficiency, and technological advancement.
  • Policymakers and Ethicists: Engaging with ethical considerations and implications of ML and computer engineering technologies.

 IMLJCE is a dynamic and inclusive forum for researchers, engineers, and stakeholders passionate about advancing knowledge, innovation, and ethical practices at the intersection of machine learning and computer engineering. Join us on this exciting journey of exploration, collaboration, and discovery as we shape the future of intelligent computing and computer engineering for the benefit of society and technology.

Abstracting and Indexing

  • Emerging Sources Citation Index (in the process)
  • Scopus
  • Indian Citation Index
  • ROAD: the Directory of Open Access scholarly Resources
  • Research Gate
  • Google Scholar
  • Academia Database
  • DPI Digital Library

Note: If your article is selected, there is an open access fee of $2000 USD, which may be waived based on the paper's quality.