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Image captioning with SEBL net: Squeeze and excitation block combined with Bi-long-short term memory network
Published in Mattingley Publishing
2019
Volume: 81
   
Issue: 11-12
Pages: 2732 - 2742
Abstract
Rapid developments in the advancing Deep Learning (DL) made significant progress in the methodologies for Automated Captioning. Automatic captioning for digital images or videos is a great challenge in Artificial intelligence. Though most algorithms used Convolution Neural networks (CNN), this work emphasize the use of Squeeze and Excitation (SE) technique with the Long Short- Term Memory (LSTM). This combination works well to generate the caption from a sequence of words based on the learning. This proposed work bridges the gap between visual and language system by combining the two vital methodologies for image caption. © 2019 Mattingley Publishing. All rights reserved.
About the journal
JournalTest Engineering and Management
PublisherMattingley Publishing
ISSN01934120