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  Published Paper Details:

  Paper Title

GENERATING CAPTIONS FOR IMAGES GIVEN BY USERS

  Authors

  Soniya Jadhav,  Swarnim Mudaliar,  Kavach Shah,  Torana Kamble

  Keywords

Computer Vision ,Object Detection Convolutional Neural Network (CNN) , Recurrent Neural Network (RNN) , Long Short Term Memory (LSTM) .

  Abstract


Recent developments in the field of computer vision and object detection have allowed for an increased interest in the concept of image caption generation. Various researchers have worked on this topic and have produced impressive results. In this paper, we discuss the latest techniques used for the generation of captions from any given input image. The paper elaborates on the latest approach towards solving the problem of caption generation, namely by focusing on the use of a Convolutional Neural Networks (CNN) based model for feature extraction and a Long-Short Term Memory (LSTM) based Recurrent Neural Network model for generating meaningful captions. Furthermore, the existence of huge datasets like Flickr30k , Kaggle and MS COCO, along with greater computational power, allow for increased accuracy in the built models.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2204560

  Paper ID - 218433

  Page Number(s) - e822-e824

  Pubished in - Volume 10 | Issue 4 | April 2022

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Soniya Jadhav,  Swarnim Mudaliar,  Kavach Shah,  Torana Kamble,   "GENERATING CAPTIONS FOR IMAGES GIVEN BY USERS", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 4, pp.e822-e824, April 2022, Available at :http://www.ijcrt.org/papers/IJCRT2204560.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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