A Neuro-Symbolic ASP Pipeline for Visual Question Answering

We present a neuro-symbolic visual question answering (VQA) pipeline for CLEVR, which is a well-known dataset that consists of pictures showing scenes with objects and questions related to them. Our pipeline covers (i) training neural networks for object classification and bounding-box prediction of...

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Vydáno v:	Theory and practice of logic programming Ročník 22; číslo 5; s. 739 - 754
Hlavní autoři:	EITER, THOMAS, HIGUERA, NELSON, OETSCH, JOHANNES, PRITZ, MICHAEL
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cambridge, UK Cambridge University Press 01.09.2022
Témata:	Answer set programming Computation theory Datasets Determinism Deterministics Encoding (symbols) Encodings Forecasting Logic programming Natural language processing Network prediction Neural networks neuro-symbolic computation Object classification Original Article Pipelines Program translators Question Answering Questions Statistical analysis Symbolic computation visual question answering neuro-symbolic computation answer-set programming visual question answering
ISSN:	1471-0684, 1475-3081, 1475-3081
On-line přístup:	Získat plný text
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