MULTI-DIMENSIONAL URBAN TRAFFIC ANOMALY EVENT RECOGNITION METHOD BASED ON TERNARY GAUSSIAN MIXTURE MODEL

• 1. 基于三元高斯混合模型的多维城市交通异常事件识别方法 [P] . 中国专利： CN110634288A . 2019-12-31
• 2. 基于自适应高斯混合模型的癌症突变簇识别方法 [P] . 中国专利： CN110890132A . 2020-03-17
• 3. Pattern recognition using gaussian mixtures based hidden markov models [P] . 欧洲知识产权局专利： EP0932143A3 . 1999-12-29

  机译： 使用基于高斯混合的隐马尔可夫模型进行模式识别

• 4. Pattern recognition using gaussian mixtures based hidden markov models [P] . 欧洲知识产权局专利： EP0932143A2 . 1999-07-28

  机译： 使用基于高斯混合的隐马尔可夫模型进行模式识别

• 5. UNSUPERVISED IMAGE-BASED ANOMALY DETECTION USING MULTI-SCALE CONTEXT-DEPENDENT DEEP AUTOENCODING GAUSSIAN MIXTURE MODEL [P] . 美国专利： US2019244337A1 . 2019-08-08

  机译： 基于多尺度上下文相关的深度自动编码高斯混合模型的基于图像的非监督异常检测

• 1. A GAUSSIAN MIXTURE MODEL-BASED REGULARIZATION METHOD IN ADAPTIVE IMAGE RESTORATION [J] . Liu Peng, Zhang Yan, Mao Zhigang 电子科学学刊（英文版） . 2007,第001期
• 2. A GAUSSIAN MIXTURE MODEL-BASED REGULARIZATION METHOD IN ADAPTIVE IMAGE RESTORATION [J] . Liu, Peng, Zhang, 电子科学学刊：英文版 . 2007,第001期
• 3. An Event Recognition Method for Ф-OTDR Based on the Gaussian Mixture Models and Hidden Markov Models [C] . Lilong Ma, Tuanwei Xu, Kaiheng Yang, Conference on advanced sensor systems and applications . 2020
• 4. Multi-dimensional Marching-Jury Backwards Beam Equation Method with uncertainty in transport parameters: Influence of non-Gaussianity and sampling network on pollution event reconstruction. [D] . Cornacchiulo, Daniel Francis. 2006
• 5. A Method for Broccoli Seedling Recognition in Natural Environment Based on Binocular Stereo Vision and Gaussian Mixture Model [O] . Luzhen Ge, Zhilun Yang, Zhe Sun, 2019
• 6. Gaussian mixture model for event recognition in optical time-domain reflectometry based sensing systems [O] . Fedorov, Aleksey, Anufriev, Maxim, Zhirnov, Andrey, 2016

• 1. Novel pseudo-divergence of Gaussian mixture models based speaker clustering method [J] . Wang Bo Xu Yiqiong . 仪器仪表学报 . 2006,第z1期
• 2. Application of a Novel Method for Machine Performance Degradation Assessment Based on Gaussian Mixture Model and Logistic Regression [J] . LIU Wenbin ,ZHONG Xin ,LEE Jay . 中国机械工程学报 . 2011,第005期
• 3. Text Independent Automatic Speaker Recognition System Using Mel-Frequency Cepstrum Coefficient and Gaussian Mixture Models [J] . Alfredo Maesa ,Fabio Garzia ,Michele Scarpiniti . 信息安全（英文） . 2012,第4期
• 4. 基于多维卡口数据的城市交通分析方法与系统 [C] . 王蓓 ,宁平华 ,段小梅 . 2018年中国城市交通规划年会 . 2018
• 5. 基于高斯混合模型的脚步声身份识别方法 [A] . 房玉杰 . 2021