Image Understanding Through Visual Question Answering: A Review from Past Research
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-64847-2_31
Reference24 articles.
1. Liu, C., Tan, Y.Y., Xia, T.T., Zhang, J., Zhu, M.: Co-attention graph convolutional network for visual question answering. Multimedia Syst. 29, 2527–2543 (2023)
2. Guo, D., Xu, C., Tao, D.: Bilinear graph networks for visual question answering. IEEE Trans. Neural Netw. Learn. Syst. 34, 1023–1034 (2021)
3. Guo, Z., Han, D.: Sparse co-attention visual question answering networks based on thresholds. Appl. Intell. 53(1), 586–600 (2023)
4. Bansal, M., Kumar, M., Sachdeva, M., Mittal, A.: Transfer learning for image classification using VGG19: caltech-101 image data set. J. Ambient Intell. Human. Comput. 1–12 (2021)
5. Ma, J., Liu, J., Lin, Q., Wu, B., Wang, Y., You, Y.: Multitask learning for visual question answering. IEEE Trans. Neural Netw. Learn. Syst. 34, 1380–1394 (2021)
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