Deep Learning Approaches Based on Transformer Architectures for Image Captioning Tasks-Reference-Cited by-同舟云学术

Deep Learning Approaches Based on Transformer Architectures for Image Captioning Tasks

Published:2022 Issue: Volume:10 Page:33679-33694
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Castro Roberto¹^ORCID,Pineda Israel¹^ORCID,Lim Wansu²^ORCID,Morocho-Cayamcela Manuel Eugenio¹^ORCID

Affiliation:

1. Deep Learning for Autonomous Driving, Robotics, and Computer Vision Research Group (DeepARC Research), School of Mathematical and Computational Sciences, Yachay Tech University, Urcuquí, Ecuador

2. Department of Aeronautics, Mechanical and Electronic Convergence Engineering, Future Communications and Systems Laboratory (FCSL), Kumoh National Institute of Technology, Gumi-si, Republic of Korea

Funder

Ministry of SMEs and Start-ups, South Korea

National Research Foundation of Korea

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09739703.pdf?arnumber=9739703

Reference34 articles.

1. Machine Learning to Improve Multi-Hop Searching and Extended Wireless Reachability in V2X

2. ImageNet: A large-scale hierarchical image database