Question aware prediction with candidate answer recommendation for visual question answering = 후보 답변 예측을 통한 영상 기반 질의응답에 대한 연구

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This paper describes a novel approach for Visual Question Answering. Our proposed network solves an open-ended problem with candidate answer recommendation, which is generated solely from the given question. Then, we combine the score from our question-aware prediction module and the score from candidate answer recommendation module to determine the final composite score. Our approach uses the bag-of-words (BOW) framework to understand questions, instead of a complex and neural-network-based module; therefore, an additional dataset to pre-train the language model is not required. Moreover, we show that the BOW framework is capable of extracting the keywords from the question. Although our proposed approach does not achieve the state-of-the-art performance overall, our approach performs the best for certain types of questions with a small amount of training data.
Advisors
Kim, Junmoresearcher김준모researcher
Description
한국과학기술원 :전기및전자공학부,
Publisher
한국과학기술원
Issue Date
2016
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 전기및전자공학부, 2016.8 ,[iv, 26 p. :]

Keywords

Deep learning; Visual question answering; Image understanding; Candidate answer recommendation; Convolution; 딥 러닝; 영상기반 질의응답; 영상 이해; 후보 답변 추천; 컨볼루션

URI
http://hdl.handle.net/10203/221700
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=663442&flag=dissertation
Appears in Collection
EE-Theses_Master(석사논문)
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