arrow
返回

Automated Image Captioning Using Sparrow Search Algorithm With Improved Deep Learning Model

delete2023-01-01
delete0
delete
OA
AI
M
Munya A. Arasi
H
Haya Mesfer Alshahrani
A
Alruwais, N
A
Abdelwahed Motwakel *
A
Abdullah Mohamed
DOI:10.1109/ACCESS.2023.3317276delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
Image captioning is a deep learning technique that intends to create and generate textual descriptions or captions for images. It integrates computer vision and natural language processing (NLP) to comprehend the visual content of an image and generate human-like descriptions. Deep learning (DL) based image captioning models can be trained on large-scale datasets, allowing them to generalize various types of images and generate captions that apply to a wide range of visual scenarios. By combining computer vision and natural language processing, DL-enabled image captioning models can understand both visual and textual information, which enables them to generate captions that not only describe the visual content but also incorporate contextual and semantic information. This study develops an Automated Image Captioning using Sparrow Search Algorithm with Improved Deep Learning (AIC-SSAIDL) technique. The major intention of the AIC-SSAIDL technique lies in the automated generation of textual captions for the input images. To accomplish this, the AIC-SSAIDL technique utilizes the MobileNetv2 model to generate feature descriptors of the input images and its hyperparameter tuning process takes place using SSA. For the image captioning process, the AIC-SSAIDL technique utilizes an attention mechanism with long short-term memory (AM-LSTM) network. Finally, the hyperparameter selection of the AM-LSTM model is performed by the fruit fly optimization (FFO) algorithm. A wide range of experiments has been conducted on benchmark data to depict the better performance of the AIC-SSAIDL method. The comprehensive result analysis highlighted the enhanced captioning results of the AIC-SSAIDL method with maximum CIDEr of 46.12, 61.89, and 137.45 on Flickr8k, Flickr30k, and MSCOCO datasets, respectively.
Keyword:
Convolutional neural networks
Visualization
Feature extraction
Convolution
Deep learning
Natural language processing
Computational modeling
Image capture
Search methods
Image captioning
deep learning
natural language processing
sparrow search algorithm
computer vision

期刊

IEEE Access 封面图
IEEE Access
IF:
3.6
论文数:
9.8W
被引数:
29.4W

机构

K
King Saud University
学者数:
3.4W
论文数: 3.8W
被引数: 815
P
Princess Nourah bint Abdulrahman University
学者数:
8.3K
论文数: 9.6K
被引数: 10
E
egyptian knowledge bank (ekb)
学者数:
11.6W
论文数: 9.3W
被引数: 84
K
King Khalid University
学者数:
1.1W
论文数: 1.3W
被引数: 1.5W
P
Prince Sattam Bin Abdulaziz University
学者数:
6.9K
论文数: 8.9K
被引数: 9.9K
学者 查看更多机构
引用论文

引用论文

err分享
err收藏
Investigation of fast processes in condensed matter by time-resolved x-ray diffraction通过时间分辨X射线衍射研究凝聚态物质中的快速过程
err2009-03-19
err0
PREAI
errI. Uschmann; T. Kämpfer; F. Zamponi; A. Lübcke; U. Zastrau; R. Loetzsch; S. Höfer; A. Morak; E. Förster
err分享
err收藏
Estudiantes con discapacidad en una universidad chilena: desafíos de la inclusión智利大学中的残疾学生:包容的挑战
err2015-10-08
err0
errOAAI
errGabriela Paulina Villafañe Hormazábal; Angélica Aurora Corrales Huenul; Valentina Javiera Soto Hernández
err分享
err收藏
err分享
err收藏
Image captioning model using attention and object features to mimic human image understanding
err2022-02-14
err25
errOAAI
errAl-Malla, Muhammad Abdelhadie; Jafar, Assef; Ghneim, Nada
err分享
err收藏
err
IF0
err
err0
PREAI
err
err分享
err收藏
Boosting convolutional image captioning with semantic content and visual relationship
err2021-12-01
err30
PREAI
errBai, Cong; Zheng, Anqi; Huang, Yuan; Pan, Xiang; Chen, Nan
err分享
err收藏
学者 查看更多内容