Authors : Monali Kapuriya; Zemi Lakkad; Satwi Shah

Volume/Issue : Volume 9 - 2024, Issue 8 - August

Google Scholar : https://tinyurl.com/2r682n3n

Scribd : https://tinyurl.com/msjaassb

DOI : https://doi.org/10.38124/ijisrt/IJISRT24AUG851

Abstract : In this have a look at, we discover the integration of Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks for the motive of image caption generation, a mission that involves a fusion of herbal language processing and computer imaginative and prescient techniques to describe images in English. Delving into the realm of photograph captioning, we meticulously investigate several fundamental concepts and methodologies associated with this area. Our technique includes leveraging prominent equipment inclusive of the Keras library, numpy, and Jupyter notebooks to facilitate the development of our studies. Furthermore, we delve into the utilization of the flickr_dataset and CNNs for image category, elucidating their significance in our examination. Through this research endeavor, we aim to make a contribution to the development of image captioning structures with the aid of combining modern-day strategies from both laptop imaginative and prescient and herbal language processing domain names.

Keywords : CNN, LSTM, Image Captioning, Deep Learning.

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