Image Caption Generator Using CNN and LSTM Hybrid Models

Image captioning refers to the automated process of generating a descriptive sentence that conveys the content of a given image. The developed model receives an image as input and produces an English sentence that accurately represents what is depicted. This area has drawn considerable attention in recent years, particularly in the realm of cognitive computing, due to its reliance on both computer vision and natural language processing techniques. The system utilizes a Convolutional Neural Network (CNN) to analyze and extract visual features from the image, which are then passed to a Long Short- Term Memory (LSTM) network responsible for constructing the descriptive sentence. The CNN functions as the encoder, while the LSTM acts as the decoder. Following caption generation, the model's performance is evaluated to ensure the quality and relevance of the output. This enables the generation of meaningful, human-readable descriptions for various images

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Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-08-08
DOI
https://doi.org/10.22214/ijraset.2025.73566
Primary Topic
Multimodal Machine Learning Applications
Type
article
Field-Weighted Citation Impact
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article

Image Caption Generator Using CNN and LSTM Hybrid Models

G. Sri Nikhila
International Journal for Research in Applied Science and Engineering Technology
Multimodal Machine Learning Applications
article

Image Caption Generator Using CNN and LSTM Hybrid Models

G. Sri Nikhila
article en

Abstract

Image captioning refers to the automated process of generating a descriptive sentence that conveys the content of a given image. The developed model receives an image as input and produces an English sentence that accurately represents what is depicted. This area has drawn considerable attention in recent years, particularly in the realm of cognitive computing, due to its reliance on both computer vision and natural language processing techniques. The system utilizes a Convolutional Neural Network (CNN) to analyze and extract visual features from the image, which are then passed to a Long Short- Term Memory (LSTM) network responsible for constructing the descriptive sentence. The CNN functions as the encoder, while the LSTM acts as the decoder. Following caption generation, the model's performance is evaluated to ensure the quality and relevance of the output. This enables the generation of meaningful, human-readable descriptions for various images

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(8)
Quality Education
Openalex Percentile: Top 80%
Multimodal Machine Learning Applications
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