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September 10, 2025

Image Caption Generator Using CNN and LSTM Hybrid Models

Key Points

The developed model generates sentences describing images, enhancing automated captioning capabilities.
Using a CNN for feature extraction and an LSTM for sentence construction, the system outputs relevant captions.
The performance of the model is evaluated to ensure quality in generated captions, highlighting its effectiveness.
Image captioning has gained attention in cognitive computing, leveraging both computer vision and language processing.

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

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Image Caption Generator Using CNN and LSTM Hybrid Models

Key Points

Abstract

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