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Continental Scholarly Publications

Journal of Artificial Intelligence, Machine Learning, and Computing

ISSN 3064-7312 Open Access Double-Blind Peer Review Impact Factor 8.878
Quarterly Frequency
Open Access Access
21 Days to First Decision
97% Author Satisfaction
6.2 Weeks to Publication
📢 Call for Papers — Submit your manuscript for the next issue!
Now Publishing
Volume 13, Issue 3  (2025)
July – September 2025
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Call for Manuscript Submissions

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Aims & Scope

The Journal of Artificial Intelligence, Machine Learning, and Computing is a peer-reviewed, open-access journal dedicated to publishing high-quality research in AI algorithms, machine learning models, computational intelligence, and their real-world applications. Our mission is to advance the frontiers of intelligent systems and promote innovative computing solutions.

Read Full Aims & Scope

Why Publish With Us

Rigorous Peer Review

Every submission undergoes double-blind review by recognised domain experts, ensuring the highest standards of scholarly rigour.

Global Visibility

Indexed in leading academic databases. Your work reaches scholars, practitioners, and decision-makers across the world.

Rapid Publication

First editorial decision within 21 days. Accepted manuscripts published within 6.2 weeks.

Recently Published Articles

Vol. 12 · No. 4 · 2024 COMPUTER VISION TECHNIQUES FOR TRAFFIC SIGN DETECTION IN ADAS APPLICATIONS
Taras Volodymyrovych Kravchenko et al.
Vol. 12 · No. 4 · 2024 DATA-DRIVEN DIAGNOSTIC TOOLS FOR BREAST CANCER DETECTION IN CLINICAL DECISION SUPPORT SYSTEMS
Oleksii Serhiyovych Bondarenko et al.
Vol. 12 · No. 4 · 2024 PERFORMANCE-DRIVEN APPROACHES TO EXPONENTIATION IN GF (2ⁿ)
Alexei Dmitrievich Morozov et al.
Vol. 12 · No. 4 · 2024 FRACTAL APPROACH FOR RESEARCHING INFORMATION EMERGENCY FEATURES OF TECHNOLOGICAL PARAMETERS
N Kharkiv Karazin et al.
Vol. 12 · No. 4 · 2024 INTEGRATING INFORMATION GAIN FOR HYBRID OPTIMIZATION IN SUPERVISED LEARNING ALGORITHMS
Ahmad Syahrul Ramadhan-Firdaus et al.
Vol. 12 · No. 4 · 2024 ACCESSIBILITY BY DESIGN: A CONTINUOUS PROCESS MODEL FOR WEB DEVELOPERS
Danylo Viktorovych Shevtsov-Lysenko et al.

Indexed & Abstracted In

Scopus
DOAJ
IEEE Xplore
ACM Digital Library

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