Comparative Study of Transformer and LSTM Network with Attention Mechanism on Image Captioning-Reference-Cited by-同舟云学术

Comparative Study of Transformer and LSTM Network with Attention Mechanism on Image Captioning

Published:2023 Issue: Volume: Page:527-539
ISSN:2367-3370
Container-title:IOT with Smart Systems
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Author:

Dandwate Pranav,Shahane Chaitanya,Jagtap Vandana,Karande Shridevi C.

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-3761-5_47

Reference27 articles.

1. Stefanini M, Cornia M, Baraldi L, Cascianelli S, Fiameni G, Cucchiara R (2021) From show to tell, a survey on image captioning

2. Takkar S, Jain A, Adlakha P (2021) Comparative study of different image captioning models. In: 2021 5th International conference on computing methodologies and communication (ICCMC), Erode, India, pp 1366–1371. https://doi.org/10.1109/ICCMC51019.2021.9418451

3. Maroju A, Doma SS, Chandarlapati L (2021) Image caption generating deep learning model. Int J Eng Res Technol. ISSN: 2278-0181

4. Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser L, Polosukhin I (2017)Attention is all you need. arXiv:1706.03762 [cs.CL] 6 Dec 2017

5. Vedantam R, Lawrence Zitnick C, Parikh D (2014) CIDEr: consensus-based image description evaluation

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