Opening Up Computer Science

Array is an international open access multidisciplinary journal encompassing a broad spectrum of topics in computer science, including

    Artificial Intelligence, Machine Learning and Robotics
    Computer Systems and Architecture
    Computer Vision, Speech and Pattern Recognition
    Control & Signal Processing
    Cyber Security
    Data, Knowledge and Intelligent Systems
    Industrial Engineering
    Interdisciplinary Applications
    Medical Informatics and Biomedical Engineering
    Microelectronics and Hardware
    Multimedia and HCI
    Networks and Communications
    Operational Research and Decision Systems
    Scientific Computing
    Software Engineering
    Theoretical Computer Science

Submissions must be novel, technically sound, and clearly presented. Array accepts both technical notes (technical notes are limited to a maximum of 10 pages in the standard Elsevier format) and regular papers. In addition to research papers presenting new results, review articles as well as discussion and opinion papers are also welcome.

Papers meeting journal criteria will undergo a single-blind review process, utilizing a minimum of two (2) external referees. Our dedicated expert editorial team, together with an editorial board of hundreds of active researchers from all areas of computer science, ensure that papers move through to publication as fast as possible without compromising on the quality of the process.

The journal audience comprises academia, industry, and practitioners. Authors are strongly encouraged to make their datasets publicly accessible via a repository of their choosing.

Software publication

We invite you to convert your open source software into an additional journal publication in Software Impacts, a multi-disciplinary open access journal. Software Impacts provides a scholarly reference to software that has been used to address a research challenge. The journal disseminates impactful and re-usable scientific software through Original Software Publications which describe the application of the software to research and the published outputs.

For more information contact us at: software.impacts@elsevier.com

Special Issue on Generative AI and Green Technology for a Sustainable Future
Submission Date: 2025-04-30

The future of Artificial Intelligence (AI) is dependent on the decisions we make today. While advancements in generative AI are impressive, AI remains a double-edged sword in the context of sustainable development. The computational demands of AI technologies can lead to significant energy consumption, presenting a challenge to ecological sustainability. This special issue aims to explore the intersection of Explainable AI (XAI) with Green AI, setting an important frontier in the development of sustainable and responsible systems. By focusing on methodologies, frameworks, and applications that enhance the transparency and eco-sustainability of AI, this issue seeks to promote the development of AI systems that are both transparent and environmentally sensitive.

This special issue invites innovative research that seeks to deepen the broader understanding of the XAI paradigm and the furthering of Green AI principles. We welcome contributions that explore the dual challenge of increasing the transparency of AI while guaranteeing the eco-sustainability of the proposed solutions. Topics of interest include, but are not limited to:

    Theoretical and empirical advancements in Explainable AI
    Green AI techniques for reducing energy consumption in AI systems
    Integrating XAI and Green AI for sustainable computing solutions
    Ethical and environmental considerations in AI system development
    Case studies and XAI applications, such as in the domains of health, environmental monitoring, and smart environments
    Tools and frameworks for evaluating the sustainability and interpretability of AI models
    Impact of XAI and Green AI on reducing bias and improving fairness in AI applications
    Strategies for incorporating domain knowledge into AI for enhanced sustainability and explainability
    Ethical, privacy, and social concerns in applying sustainable AI systems
    Future directions for aligning AI with sustainability

Guest editors:

Irina Trubitsyna, PhD
DIMES, University of Calabria, Arcavacata di Rende, Italy
Email: irina.trubitsyna@dimes.unical.it 

Seyed Ali Ghorashi, PhD
University of East London, London, UK
Email: S.A.Ghorashi@uel.ac.uk

Reza Shahbazian, PhD
DIMES, University of Calabria, Arcavacata di Rende, Italy
Email: reza.shahbazian@dimes.unical.it 

Manuscript submission information:

The journal's submission platform (Editorial Manager®) will be open for submissions to this Special Issue from November 1st, 2024. Please refer to the Guide for Authors to prepare your manuscript and select the article type of “VSI: GenAI and Green Tech” when submitting your manuscript online. Both the Guide for Authors and the submission portal could be found on the Journal Homepage: Array | Journal | ScienceDirect.com by Elsevier. 

This Special Issue offers 50% APC discount.

Timeline:

Submission Open Date *01/11/2024
Final Manuscript Submission Deadline *30/04/2025
Editorial Acceptance Deadline *31/08/2025

Keywords:

Artificial Intelligence, Explainable AI, Green AI, Generative AI, Sustainable

Special Issue on Recent Advances and Applications in Image Colorization with Deep Learning
Submission Date: 2025-12-31

Image coloring is the process of converting a grayscale image into a color image with natural sensory and visual quality. Image coloring task is a classic computer vision problem, especially, infrared image colorization it has been widely concerned by scholars. Infrared image is obtained by detecting infrared radiation, and it is widely used in military, security monitoring, medicine and geological exploration. However, due to the special nature of infrared images, they lack color information, so coloring infrared images can make it easier for observers to understand and analyze image content. In recent years, image coloring technology has made important progress in the field of natural image and infrared image, especially the latest image coloring algorithms based on deep learning, are constantly proposed, which is of great significance for many application fields, such as medical diagnosis, remote sensing, artistic creation, night vision and other special application fields.  
Full scope of the Special Issue: 

    Image colorization based on deep learning
    Image colorization based on color transfer
    Image colorization based on scribble
    Image colorization based on multi-modal image fusion
    Spectral recovery or colorization of remote sensing image
    Natural image colorization
    Image colorization in biomedical engineering
    Real time applications of image colorization
    Image enhancement
    Low quality image processing

Guest editors:

Xin Jin, PhD
Yunnan University, Kunming, China
Email: xinjin@ynu.edu.cn

Qian Jiang, PhD
Yunnan University, Kunming, China
Email: jiangqian@ynu.edu.cn

Shin-Jye Lee, PhD
National Yang Ming Chiao Tung University, Hsinchu, Taiwan
Email: camhero@gmail.com

Michal Wozniak, PhD
Wroclaw University of Science and Technology, Wroclaw, Poland
Email: michal.wozniak@pwr.edu.pl

Tai Yonghang, PhD
Yunnan Normal University, Kunming, China 
Email: taiyonghang@126.com

Manuscript submission information:

The journal's submission platform (Editorial Manager®) will be open for submissions to this Special Issue from January 10th, 2025. Please refer to the Guide for Authors to prepare your manuscript and select the article type of “VSI: Image colorization” when submitting your manuscript online. Both the Guide for Authors and the submission portal could be found on the Journal Homepage: Array | Journal | ScienceDirect.com by Elsevier. 

This Special Issue offers 50% APC discount.

Timeline:

Submission Open Date *10/01/2025
Final Manuscript Submission Deadline *31/12/2025
Editorial Acceptance Deadline *30/04/2026

Keywords:

Image colorization, Artificial Intelligence, Deep learning, Neural networks, Machine learning