A survey on image captioning methods

Image captioning is a task that Involves Natural Language Processing concepts to recognize the context of an image and describe them in a natural language like English. It requires good knowledge of Deep learning. Python, working on Jupyter notebooks, Keras library, Numpy, and Natural language processing It is a Python based project where we will use deep learning techniques of Convolutional Neural Networks and a type of Recurrent Neural Network (LSTM) together. The biggest challenge is most definitely being able to create a description that must capture not only the objects contained in an image, but also express how these objects relate to each other. Automatically describing the content of an image is a fundamental problem in artificial intelligence that connects computer vision and natural language processing here, we present a generative model based on a deep recurrent architecture that combines recent advances in computer vision and machine translation and that can be used to generate natural sentences describing an image. It could have great impact, for instance by helping visually impaired people better understand the content of images on the web.

Authors

Publication Details

Journal
World Journal of Advanced Research and Reviews
Published
2025-05-26
DOI
https://doi.org/10.30574/wjarr.2025.26.2.1705
Primary Topic
Multimodal Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A survey on image captioning methods

Kotla Pranay Teja, Puthuru Kavya, B Sai, Kavitha Soppari
World Journal of Advanced Research and Reviews
Multimodal Machine Learning Applications
article

A survey on image captioning methods

Kotla Pranay Teja, Puthuru Kavya, B Sai, Kavitha Soppari
article en

Abstract

Image captioning is a task that Involves Natural Language Processing concepts to recognize the context of an image and describe them in a natural language like English. It requires good knowledge of Deep learning. Python, working on Jupyter notebooks, Keras library, Numpy, and Natural language processing It is a Python based project where we will use deep learning techniques of Convolutional Neural Networks and a type of Recurrent Neural Network (LSTM) together. The biggest challenge is most definitely being able to create a description that must capture not only the objects contained in an image, but also express how these objects relate to each other. Automatically describing the content of an image is a fundamental problem in artificial intelligence that connects computer vision and natural language processing here, we present a generative model based on a deep recurrent architecture that combines recent advances in computer vision and machine translation and that can be used to generate natural sentences describing an image. It could have great impact, for instance by helping visually impaired people better understand the content of images on the web.

World Journal of Advanced Research and ReviewsVol. 26(2)
Openalex Percentile: Top 90%
Multimodal Machine Learning Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.