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A multi-modal mixed-state dynamic Bayesian network for robust meeting event recognition from disturbed data

机译：一种多模态混合状态动态贝叶斯网络，用于从受干扰的数据中进行稳健的会议事件识别

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Marc Al-hames; Gerhard Rigoll; Technische Universität München;
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年度 2005
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1. Context augmented Dynamic Bayesian Networks for event recognition [J] . Xiaoyang Wang, Qiang Ji Pattern recognition letters . 2014,第jula1期

机译：上下文增强动态贝叶斯网络用于事件识别
2. Personal Event Management among Multiple Devices Based on User Intention Recognition Using Dynamic Bayesian Networks [J] . Hocheol JEON, Taehwan KIM, Joongmin CHOI IEICE transactions on information and systems . 2011,第7期

机译：基于动态贝叶斯网络的用户意图识别的多设备间个人事件管理
3. Personal Event Management among Multiple Devices Based on User Intention Recognition Using Dynamic Bayesian Networks [J] . Hocheol JEON, Taehwan KIM, Joongmin CHOI IEICE Transactions on Information and Systems . 2011,第7期

机译：基于动态贝叶斯网络的用户意图识别的多设备间个人事件管理
4. A Multi-Modal Mixed-State Dynamic Bayesian Network for Robust Meeting Event Recognition from Disturbed Data [C] . Al-Hames, M., Rigoll, . 2005

机译：一种多模态混合状态动态贝叶斯网络，用于从扰动数据中进行鲁棒的会议事件识别
5. Noise robust speech recognition using dynamic synapse neural networks. [D] . Heidari Namarvar, Hassan. 2005

机译：使用动态突触神经网络的噪声鲁棒语音识别。
6. Quantifying sleep architecture dynamics and individual differences using big data and Bayesian networks [O] . Benjamin D. Yetton, Elizabeth A. McDevitt, Nicola Cellini, -1

机译：使用大数据和贝叶斯网络量化睡眠体系结构动力学和个体差异
7. Robust multi-modal group action recognition in meetings from disturbed videos with the asynchronous hidden Markov model [O] . Marc Al-hames, Claus Lenz, Stephan Reiter, 2007

机译：使用异步隐马尔可夫模型在受干扰视频的会议中进行稳健的多模态群体动作识别

A multi-modal mixed-state dynamic Bayesian network for robust meeting event recognition from disturbed data

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