Iran Journal of Computer Science

Aims & Scope

Modern society is becoming more and more dependent on software systems, which in turn are getting larger and larger and more and more complex.

This poses new challenges for various areas of computer science in general and software engineering in particular; for example, trusted computing, distributed computing, cloud and fog computing, security, mobility, big data management, online social networks, to name just a few.

As such, new concepts and methodologies are required to enhance the development of software systems from both a theoretical and a practical point of view.

The Iran Journal of Computer Science aims to serve the academic research community around the globe by publishing high-quality scientific articles that present original theoretical research findings, as well as methods, techniques, tools, implementations, and applications.

It especially welcomes contributions from researchers living in or originating from Iran or the Middle East.

The journal offers a forum for researchers, professionals, and industrial practitioners to share their rapidly developing knowledge and report on the latest theoretical and practical advances in computer science, with a particular focus on the theoretical foundations and practical aspects of software engineering.

Articles that highlight advances in the use of computer science methods and technologies for solving tasks in other sciences are also welcomed.

View Aims & Scope

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Metrics & Ranking

Journal Rank

Year	Value
2024	14819

Journal Citation Indicator

Year	Value
2024	239

SJR (SCImago Journal Rank)

Year	Value
2024	0.362

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	19

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Mango leaf disease recognition using neural network and support vector machine

  Citation: 109

  Authors: Md. Rasel, Sujit, Subrata Kumar, Md. Atikur

• Hybrid stacked ensemble combined with genetic algorithms for diabetes prediction

  Citation: 83

  Authors: Jafar, Babak

• A hybrid method for heart disease diagnosis utilizing feature selection based ensemble classifier model generation

  Citation: 55

  Authors: Jafar, Babak

• Heart disease prediction using distinct artificial intelligence techniques: performance analysis and comparison

  Citation: 54

  Authors: Md. Imam, Mehadi Hasan, Md. Ashikur Rahman, Farida Siddiqi, Sharmin, Md. Sabbir, Md. Ahnaf Sad

• Deep understanding of 3-D multimedia information retrieval on social media: implications and challenges

  Citation: 47

  Authors: Ritika, Vishal, Gagandeep Singh, Anupam

• Block-based copy–move image forgery detection using DCT

  Citation: 45

  Authors: Azra, Zishan Husain, Syed Naseem

• Advanced AI-driven emergency response systems for enhanced vehicle and human safety

  Citation: 44

  Authors: N., N., S., S., S., K. Martin, Binay Kumar, Digvijay

• ECG signal analysis using CWT, spectrogram and autoregressive technique

  Citation: 40

  Authors: Varun, Monika, Vikas, Anshu

• Blockchain-based security management of IoT infrastructure with Ethereum transactions

  Citation: 37

  Authors: S. K. Tanzir, Abdullah Al Mamun, Mohammad Badrul Alam

• A review of various semi-supervised learning models with a deep learning and memory approach

  Citation: 33

  Authors: Jamshid, Hasan

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