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Integrating parametric and non-parametric models for scene labeling
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015We adopt Convolutional Neural Networks (CNN) as our parametric model to learn discriminative features and classifiers for local patch classification. As visually similar pixels are indistinguishable from local context, we alleviate such ambiguity by introducing a global scene constraint.
Bing Shuai +4 more
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Dynamic parametric modeling-based model updating strategy of aeroengine casings
Chinese Journal of Aeronautics, 2021Cheng-Wei Fei, Cheng Lu, Li-Qiang An
exaly
Evaluating Model Specification When Using the Parametric G-Formula in the Presence of Censoring.
American Journal of Epidemiology, 2023Yu-Han Chiu, Issa J Dahabreh, Lan Wen
exaly
Extremes: Spatial Parametric Modeling
2012Statistics of spatial extremes is developing very rapidly, owing to the demands of applications in the environmental sciences and the insurance and risk industries. This entry sketches the main ideas, based on classical extreme-value statistics. The two main threads of work are the fitting of max-stable models to spatial extremes, and the use of latent
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Parametric model order reduction based on parallel tensor compression
International Journal of Systems Science, 2021Yaolin Jiang
exaly
New support vector algorithms with parametric insensitive/margin model
Neural Networks, 2010Pei-Yi Hao
exaly