机译:通过多模式分层内存周度网络应答的长期视频问题
Hangzhou Dianzi Univ Key Lab Complex Syst Modeling & Simulat Sch Comp Sci & Technol Hangzhou 310018 Peoples R China|Zhejiang Univ Finance & Econ Sch Informat Dongfang Coll Haining 314408 Peoples R China;
Hangzhou Dianzi Univ Key Lab Complex Syst Modeling & Simulat Sch Comp Sci & Technol Hangzhou 310018 Peoples R China;
Hangzhou Dianzi Univ Key Lab Complex Syst Modeling & Simulat Sch Comp Sci & Technol Hangzhou 310018 Peoples R China;
Univ Chinese Acad Sci Sch Comp & Control Engn Beijing 101408 Peoples R China;
Noahs Ark Lab Huawei 518129 Peoples R China;
Knowledge discovery; Cognition; Visualization; Task analysis; Semantics; Engines; Computational modeling; Long-term; video question answering; multimodal; hierarchical; memory network; shallow inference; coarse-grained; fine-grained; in-depth reasoning;
机译:通过动态分层增强网络进行长视频提问
机译:内存增强了用于视频问题的深度经常性神经网络
机译:动态内存网络增强了对问题的理解,可用于文本问题解答
机译:双向注意力记忆网络,用于知识库的问答
机译:推断回答质量,回答者专业知识以及对问题进行回答的社交网络的排名。
机译:通过分层周度神经网络模型从中药处方检测疗效特异性草药群体
机译:关于知识库的问题回答的双向周度记忆网络
机译:连接对话的第一步:在自由文本问题和预先录制的视频答案之间进行调解