Turkish Journal of Computer and Mathematics Education
Journal license

Journal

Turkish Journal of Computer and Mathematics Education


Volume
& Issue

Volume 15, Issue 3


Published
on


Pages

266-277


DOI

Article

Image Caption Generator Using Cnn and Lstm

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Authors

Busani Sravani Affiliation:
Department Of CSE, Malla Reddy Engineering College for Women
, S. Sreepragna Affiliation:
Department Of CSE, Malla Reddy Engineering College for Women
, R. Madhuri Affiliation:
Department Of CSE, Malla Reddy Engineering College for Women
and V. Roja Affiliation:
Department Of CSE, Malla Reddy Engineering College for Women


Abstract

Machine learning is now all the rage in the AI world. We have recently used AI to construct very clever devices with exceptional performance. Deep learning is a subset of machine learning that produces very accurate findings, which in turn indicates very good performance. Apps for picture description make use of deep learning in our study. Providing a description of a picture's content is what image description is all about. Object and action detection in the input picture is the foundation of the notion. When describing images, there are primarily two methods: bottom-up and top-down. Bottom-up methods create captions by combining the information of an input picture. Using different architectures, such as recurrent neural networks, top-down methods provide a semantic representation of an input picture, which is then translated into a caption. One potential advantage of picture description is that it might aid those with visual impairments in comprehending what is shown in online images. What follows is an explanation of the specifics. Looking at the image below, what can you make out?


Keywords


Citation

Sravani, B., Sreepragna, S., Madhuri, R., & Roja, V. (2024). Image caption generator using cnn and lstm. Turkish Journal of Computer and Mathematics Education, 15(3), 266–277. https://doi.org/10.61841/turcomat.v15i3.14800

Published by: Engineering Journals

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