Deep learning for underwater object detection: From CNNs to transformer-based real-time solutions

Bhandari, Hari and Liu, Pengcheng orcid.org/0000-0003-0677-4421 (Accepted: 2025) Deep learning for underwater object detection: From CNNs to transformer-based real-time solutions. In: The 30th International Conference on Automation and Computing (ICAC 2025). IEEE (In Press)

Metadata

Item Type: Proceedings Paper
Authors/Creators:
Copyright, Publisher and Additional Information:

This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy.

Dates:
  • Accepted: 18 June 2025
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Computer Science (York)
Funding Information:
Funder
Grant number
EPSRC
EP/Y000773/1
Depositing User: Pure (York)
Date Deposited: 24 Jun 2025 16:00
Last Modified: 24 Jun 2025 16:00
Status: In Press
Publisher: IEEE
Open Archives Initiative ID (OAI ID):

Download

Accepted Version


Embargoed until: 29 August 2025

Filename: conference_latex_template_1_.pdf

Description: conference_latex_template (1)

Licence: CC-BY 2.5

Request a copy

file not available

Export

Statistics