Open AccessReal Time Image Captaioning
Author(s) -
Guosheng Ren,
R Sumanth,
Asha Chowdary,
A. Shashank,
T. Sravan
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.f4566.049620
Subject(s) - computer science , artificial intelligence , generator (circuit theory) , image (mathematics) , transfer of learning , recurrent neural network , machine learning , pattern recognition (psychology) , computer vision , artificial neural network , power (physics) , physics , quantum mechanics
Image caption generator means it will generate a description for the images. It will predict what is happing in the images. We make our model using a hybrid CNN-RNN model in which in the CNN part of the model we use inception model for transfer learning and RNN is majorly used for language modeling. We use Flickr8k Dataset for training and testing the model. We use LSTM model in RNN to avoid the problem of vanishing or exploding gradient in the training phase.