Image Captioning - A Deep Learning Approach Using CNN and LSTM Network-Reference-Cited by-同舟云学术

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Image Captioning - A Deep Learning Approach Using CNN and LSTM Network

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 3rd International Conference on Pervasive Computing and Social Networking (ICPCSN)
language:
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Author:

Voditel Preeti¹,Gurjar Aparna¹,Pandey Aakansha¹,Jain Akrati¹,Sharma Nandita¹,Dubey Nisha¹

Affiliation:

1. Shri Ramdeobaba College of Engineering and Management,Department of Computer Applications,Nagpur,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10265860/10265772/10265997.pdf?arnumber=10265997

Reference15 articles.

1. Image Captioning Using Deep Convolutional Neural Networks (CNNs)

2. Improving Image Captioning with Better Use of Caption

3. Hybrid Architecture using CNN and LSTM for Image Captioning in Hindi Language

4. Image Captioning with Deep Bidirectional LSTMs

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Image Caption Generation Through the Integration of CNN-Based Residual Network Architectures and LSTM;2024 7th International Conference on Informatics and Computational Sciences (ICICoS);2024-07-17

2. Visio-Voice Transforming Images into Sound for the Visually Impaired;2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS);2024-06-28

3. Visual Literacy Reinvented: A CNN-LSTM Approach for E-Learning;2024 1st International Conference on Communications and Computer Science (InCCCS);2024-05-22

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