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Automatic Image Caption Generation Using CNN, RNN and LSTM

S.S. Pophale1 , Praveen Mokate2 , Sandip Najan3 , Sandesh Gajare4 , Sanket Swami5

Section:Research Paper, Product Type: Journal Paper
Volume-9 , Issue-8 , Page no. 60-62, Aug-2021

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v9i8.6062

Online published on Aug 31, 2021

Copyright © S.S. Pophale, Praveen Mokate, Sandip Najan, Sandesh Gajare, Sanket Swami . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: S.S. Pophale, Praveen Mokate, Sandip Najan, Sandesh Gajare, Sanket Swami, “Automatic Image Caption Generation Using CNN, RNN and LSTM,” International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.60-62, 2021.

MLA Style Citation: S.S. Pophale, Praveen Mokate, Sandip Najan, Sandesh Gajare, Sanket Swami "Automatic Image Caption Generation Using CNN, RNN and LSTM." International Journal of Computer Sciences and Engineering 9.8 (2021): 60-62.

APA Style Citation: S.S. Pophale, Praveen Mokate, Sandip Najan, Sandesh Gajare, Sanket Swami, (2021). Automatic Image Caption Generation Using CNN, RNN and LSTM. International Journal of Computer Sciences and Engineering, 9(8), 60-62.

BibTex Style Citation:
@article{Pophale_2021,
author = {S.S. Pophale, Praveen Mokate, Sandip Najan, Sandesh Gajare, Sanket Swami},
title = {Automatic Image Caption Generation Using CNN, RNN and LSTM},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {8 2021},
volume = {9},
Issue = {8},
month = {8},
year = {2021},
issn = {2347-2693},
pages = {60-62},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5380},
doi = {https://doi.org/10.26438/ijcse/v9i8.6062}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v9i8.6062}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5380
TI - Automatic Image Caption Generation Using CNN, RNN and LSTM
T2 - International Journal of Computer Sciences and Engineering
AU - S.S. Pophale, Praveen Mokate, Sandip Najan, Sandesh Gajare, Sanket Swami
PY - 2021
DA - 2021/08/31
PB - IJCSE, Indore, INDIA
SP - 60-62
IS - 8
VL - 9
SN - 2347-2693
ER -

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Abstract

The paper aims at generating automated captions by learning the contents of the image. At present images are annotated with human intervention and it becomes nearly impossible task for huge commercial databases. The image database is given as input to a deep neural network (Convolutional Neural Network (CNN)) encoder for generating “thought vector” which extracts the features and nuances out of our image and RNN (Recurrent Neural Network) decoder is used to translate the features and objects given by our image to obtain sequential, meaningful description of the image .In this paper we are going to explain the survey about image captioning and our proposed system.

Key-Words / Index Term

image annotation, deep learning, CNN, RNN, LSTM, python3, flask, etc.

References

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