10th International Conference on Deep Learning Technologies (ICDLT 2026)

Rosa Fox
Description

Publication
All accepted papers of ICDLT 2026 will be published in the ACM International Conference Proceedings and submitted for indexing in Ei Compendex and Scopus.
The ICDLT series has maintained a consistent record of successful indexing in previous years:
ICDLT 2025 Proceedings – 979-8-4007-1852-6 | ACM Digital Library | Ei & SCOPUS Index
ICDLT 2024 Proceedings – 979-8-4007-1686-7 | ACM Digital Library | Ei & SCOPUS Index
ICDLT 2023 Proceedings – 979-8-4007-0752-0 | ACM Digital Library | Ei & SCOPUS Index
ICDLT 2022 Proceedings – 978-1-4503-9693-6 | ACM Digital Library | Ei & SCOPUS Index
ICDLT 2021 Proceedings – 978-1-4503-9016-3 | ACM Digital Library | Ei & SCOPUS Index
ICDLT 2020 Proceedings – 978-1-4503-7548-1 | ACM Digital Library | Ei & SCOPUS Index
ICDLT 2019 Proceedings – 978-1-4503-7160-5 | ACM Digital Library | Ei & SCOPUS Index
ICDLT 2018 Proceedings – 978-1-4503-6473-7 | ACM Digital Library | Ei & SCOPUS Index
For more details, please visit: https://www.icdlt.org/pub.html

Call for paper
Track 1: Deep Learning Model and Algorithm
Track 2: Machine Learning Theory and Technology
Track 3: Deep and Machine Learning Applications
Track 4: Responsible AI, Security, and Governance
Full topic list available at: http://www.icdlt.org/cfp.html

Submission
Full Paper Submission (Author Participation): Accepted papers will be published in the conference proceedings. Authors must present their work orally or via poster at the conference.
Abstract Submission (Presenter Participation): Presentation only (no publication).
Listener Participation: Attend all sessions and receive a listener certificate.

Submission System: https://www.zmeeting.org/submission/icdlt2026
Submission Email: icdlt@young.ac.cn
Templates: https://icdlt.org/acm_template.docx; https://icdlt.org/LaTeX-Templates.zip
For detailed submission guidelines, visit: https://icdlt.org/sub.html

Contact
Conference Secretary: Ms. Wu
Email: icdlt@young.ac.cn
Phone: +86-132-9000-0002

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