ISSN (Online) : 2456 - 0774

Email : ijasret@gmail.com

ISSN (Online) 2456 - 0774

DESIGN AND TRAIN CAPTION FROM IMAGES BYUSING DEEP LEARNING APPROACH

Abstract

Abstract: Picture subscription is an enterprise which involves both visual and linguistic understanding. To build words inhuman languages, image models have to interpret visual content. The focus approach has been used extensive in imagesubtitles because it can give deeper sequential model training with more accurate picture information. It is a crucial andtough challenge to use natural languages to describe the image content automatically. It has several possibilities. Forinstance, it might help understand the substance of the image. It can also provide higher precision and succinct pictureinformation in cases such as picture sharing in social network platforms. In this study, deep neural networks are employed toachieve this goal. A convolutionary neural network (CNN) is utilized to extract vectors from real time video (image frames)and an LSTM network for generating substitutes from these vectors is employed. The Flickr 8K dataset is the most often useddataset to assess the model. It consist of over 8k photographs. The methodology creates picture captions which are generatedby gathering information from pairs of images and captions.Keywords: Convolutional Neural Networks (CNN); Long Short-Term Memory networks (LSTM); Recurrent neural networks(RNN); Deep neural networks (DNNs).

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Paper Submission Open For October 2024
UGC indexed in (Old UGC) 2017
Last date for paper submission 30th October, 2024
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Publication of Paper Within 15-30 Days after completing all the formalities
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