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2021 | OriginalPaper | Buchkapitel

AI Explainability. A Bridge Between Machine Vision and Natural Language Processing

verfasst von : Mourad Oussalah

Erschienen in: Pattern Recognition. ICPR International Workshops and Challenges

Verlag: Springer International Publishing

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Abstract

This paper attempts to present an appraisal review of explainable Artificial Intelligence research, with a focus on building a bridge between image processing community and natural language processing (NLP) community. The paper highlights the implicit link between the two disciplines as exemplified from the emergence of automatic image annotation systems, visual question-answer systems. Text-To-Image generation and multimedia analytics. Next, the paper identified a set of natural language processing fields where the visual-based explainability can boost the local NLP task. This includes, sentiment analysis, automatic text summarization, system argumentation, topical analysis, among others, which are highly expected to fuel prominent future research in the field.

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Vorheriges Kapitel Reliability of eXplainable Artificial Intelligence in Adversarial Perturbation Scenarios

Nächstes Kapitel Recursive Division of Image for Explanation of Shallow CNN Models

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Titel: AI Explainability. A Bridge Between Machine Vision and Natural Language Processing
verfasst von: Mourad Oussalah
Verlag: Springer International Publishing
Buch: Pattern Recognition. ICPR International Workshops and Challenges
Print ISBN: 978-3-030-68795-3

Electronic ISBN: 978-3-030-68796-0

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-3-030-68796-0_19

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