Visual Question Answering
From Theory to Application
Visual Question Answering (VQA) usually combines visual inputs like image and video with a natural language question concerning the input and generates a natural language answer as the output. This is by nature a multi-disciplinary research problem, involving computer vision (CV), natural language processing (NLP), knowledge representation and reasoning (KR), etc.Further, VQA is an ambitious undertaking, as it must overcome the challenges of general image understanding and the question-answering task, as well as the difficulties entailed by using large-scale databases with mixed-quality inputs. However, with the advent of deep learning (DL) a…
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Produktdetails
Weitere Autoren: Wang, Peng / Zhu, Wenwu / He, Xiaodong / Wang, Xin
- ISBN: 978-981-1909-63-4
- EAN: 9789811909634
- Produktnummer: 38905573
- Verlag: Springer Nature Singapore
- Sprache: Englisch
- Erscheinungsjahr: 2022
- Seitenangabe: 252 S.
- Masse: H24.1 cm x B16.0 cm x D1.9 cm 547 g
- Auflage: 1st ed. 2022
- Abbildungen: HC runder Rücken kaschiert
- Gewicht: 547
Über den Autor
152181049
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