Skip to main content Skip to main navigation menu Skip to site footer

International Journal of Deep Learning

ISSN 2685-4600 (Online)
  • Home
  • About
  • Login
  • Register
  • Search
  • Current
  • Archives
  • Announcements
  • Statistics
  • Indexing & Abstracting
  • Contact
  1. Home
  2. About the Journal

About the Journal

People

  • Contact
  • Editorial Team
  • Peer Reviewers

Policies

  • Focus and Scope
  • Section Policies
  • Peer Review Process
  • Publication Frequency
  • Open Access Policy
  • Archiving
  • Screening for Plagiarism
  • Publication Ethics and Malpractice Statement
  • Reviewer Guidelines

Submissions

  • Online Submissions
  • Author Guidelines
  • Copyright Notice
  • Privacy Statement
  • Author Fees

Other

  • Journal Sponsorship
  • Journal History
  • Site Map
  • About this Publishing System
  • Statistics

Current issue

Issue information will be published here once the first issue is released.

View archive

Links

  • Online Submission
  • Submission Guidelines
  • Author Fees
  • Publication Ethics
  • Screening for Plagiarism
  • Editorial Board
  • Peer Reviewers
  • Review Guidelines
  • Open Access Policy
  • Visitor Statistics

Template and guidelines

s Article template s Submission guide

User

Suggested tools

  • Mendeley
  • Zotero
  • JabRef
  • Grammarly

INDEXING

  • Google Scholar
  • WorldCat
  • Dimensions
  • Wizdom
  • ISSN
  • Garda Rujukan Digital (Garuda)

CHECK FOR PLAGIARISM

  • Plagiarism Checker X

CROSSREF INFORMATION

  • Crossref Member

ISSN ACSIE

  • ISSN(ONLINE)BARCODE

Journal content

Browse By issue By author By title Other journals
ACSIE

The ACSIE (International Journal of Application Computer Science and Informatic Engineering) (e-ISSN 2685-4600; p-ISSN xxxx-xxxx) is published by INFOTEKS (Information Technology, Computer and Sciences). The content of this website is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This journal is managed using the Open Journal Systems (OJS) platform developed by the Public Knowledge Project, ensuring a transparent and efficient editorial and peer-review process.

Powered by Open Journal Systems