Experiential Questioning for VQA

Author:

Gómez Blanco Ruben,Pérez Peinador Adrián,Sanjuan Espejo Adrián,Sánchez-Ruiz Antonio A.ORCID,Díaz-Agudo BelénORCID

Publisher

Springer Nature Switzerland

Reference21 articles.

1. Agrawal, A., Batra, D., Parikh, D., Kembhavi, A.: Don’t just assume; look and answer: overcoming priors for visual question answering. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4971–4980 (2018)

2. Antol, S., et al.: VQA: visual question answering. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2425–2433 (2015)

3. Lecture Notes in Computer Science;K Basu,2020

4. Caro-Martínez, M., Wijekoon, A., Díaz-Agudo, B., Recio-García, J.A.: The current and future role of visual question answering in explainable artificial intelligence. In: Malburg, L., Verma, D. (eds.) Proceedings of the Workshops at the 31st International Conference on Case-Based Reasoning (ICCBR-WS 2023) Co-located with the 31st International Conference on Case-Based Reasoning (ICCBR 2023), Aberdeen, Scotland, UK, 17 July 2023. CEUR Workshop Proceedings, vol. 3438, pp. 172–183. CEUR-WS.org (2023). https://ceur-ws.org/Vol-3438/paper_13.pdf

5. Ester, M., Kriegel, H., Sander, J., Xu, X.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: Simoudis, E., Han, J., Fayyad, U.M. (eds.) Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), Portland, Oregon, USA, pp. 226–231. AAAI Press (1996). http://www.aaai.org/Library/KDD/1996/kdd96-037.php

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