Image Captioning with Deep Bidirectional LSTMs

Image Caption Generation Using Contextual Information Fusion ...

INDEX TERMS Bi-LSTM, image caption generation, semantic fusion, semantic similarity. ... the deep neural network based on LSTM [16] simply con-.

Image Captioning with Deep Bidirectional LSTMs and Multi-Task ...

Abstract: Data through water transfer rates are generally low due to limited bandwidth. The sonar images must be efficiently compressed to increase onboard ...

Image Captioning with Deep Bidirectional LSTMs. - DBLP

Cheng Wang, Haojin Yang, Christian Bartz , Christoph Meinel: Image Captioning with Deep Bidirectional LSTMs. ACM Multimedia 2016: 988-997.

Improving Myanmar Image Caption Generation Using NASNetLarge ...

Improving Myanmar Image Caption Generation Using NASNetLarge and Bi-directional LSTM ... This paper proposed a deep learning-based Myanmar image captioning ...

Bidirectional LSTM approach to image captioning with scene features

More recently, it has been driven by encoder decoder deep learning approaches where visual features are learned with a convolutional neural ...

Bi-LS-AttM: A Bidirectional LSTM and Attention Mechanism Model ...

(2016, January 15–19). Image captioning with deep bidirectional LSTMs. Proceedings of the 24th ACM international conference on Multimedia, Amsterdam, The ...

Image Captioning Using Motion-CNN with Object Detection - PMC

Image Captioning with Deep Bidirectional LSTMs; Proceedings of the ACM International Conference on Multimedia; Amsterdam, The Netherlands ...

Research Topics in Image Captioning using Deep Learning - S-Logix

Currently, CNN, LSTM, and combined CNN-RNN models are exploited for stylized caption generation. Some other deep learning networks-based captions for the whole ...

An Attention Mechanism and GRU Based Deep Learning Model for ...

Meinel, Image Captioning with Deep Bidirectional LSTMs and Multi-Task Learning, ACM Trans. Multimed. Comput. Commun. Appl. 14(2s) (2018). doi: 10.1145 ...

Image Caption using VGG model and LSTM

Abstract. Deep convolutional networks and recurrent neural networks have gained significant popularity in the field of image captioning ...

(PDF) Image Captioning using CNN and LSTM - Academia.edu

In the model we proposed, we examine the deep neural networks-based image caption generation technique. We give image as input to the model, the technique ...

Novel concept-based image captioning models using LSTM ... - Nature

Then, their approach used bidirectional LSTM for generating caption words. ... A comprehensive survey of deep learning for image captioning. ACM ...

Automatic Image Captioning Using Different Variants of the Long ...

Automatic Image Captioning Using Different Variants of the Long Short-Term Memory (LSTM) Deep Learning Model ... Furthermore, it was found that the bidirectional ...

A Guide to Image Captioning - Towards Data Science

... Deep Learning domain. Image captioning has a huge amount ... Most studies use Bidirectional RNNs and LSTMs for better results.

Automatic Image Captioning Using Convolution Neural Networks ...

[5]. Wang Cheng et al 2016 Image captioning with deep bidirectional LSTMs Proceedings of the 2016 ACM on Multimedia Conference. ACM. CrossrefGoogle Scholar. [6].

Changing a CNN-LSTM image captioning architecture to use BiLSTMs

So after doing a bit of research, I finally found out why the model is not working at all when I change the LSTM to Bi-LSTM.

A Dual Prediction Network for Image Captioning - Li Liu

5: Example of image captioning using Bi-LSTM and Bi-DPN. ... [7] Cheng Wang, Haojin Yang, Christian Bartz, and Christoph. Meinel, “Image captioning with deep ...

‪Cheng Wang‬ - ‪Google Scholar‬

Image Captioning with Deep Bidirectional LSTMs and Multi-Task Learning. C Wang, H Yang, C Meinel. ACM Transactions on Multimedia Computing, Communications, and ...

Image captioning using attention network and machine learning ...

C. (. 2018. ). Image Captioning with Deep Bidirectional LSTMs and Multi-Task Learning . ACM Transactions on Multimedia Computing ...

DAA: Dual LSTMs with adaptive attention for image captioning

Feature vectors of image are generally extracted by deep convolutional neural networks(CNN) [1], [2] and then used to co-embed images and text ...