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搜索结果: 1-12 共查到Feature Space相关记录12条 . 查询时间(0.128 秒)
A new information extraction method of damaged buildings rooted in optimal feature space is put forward on the basis of the traditional object-oriented method. In this new method, ESP (estimate of sca...
Many scholars at home and abroad are extensive concerning about the forming mechanical of urban heat island phenomenon. According to correlation study, the surface temperature in the center of Beijing...
This thesis analyzes the anomalous measurement metric in high dimension feature space, where it is supposed the Gaussian assumption for state-of-art mahanlanobis algorithms is reasonable. The realizat...
We propose a novel approach, Sequential Lasso, for feature selection in linear regression models with ultra-high dimensional feature spaces.
Gabor feature space is elaborated for representation,processing and segmentation of textured images. As a first step of preprocessing of images represented in this space, we introduce an algorithm for...
Gabor feature space is elaborated for representation,processing and segmentation of textured images. As a first step of preprocessing of images represented in this space, we introduce an algorithm for...
Gabor Analysis is frequently used for texture analysis and segmentation. Once the Gaborian feature space is generated it may be interpreted in various ways for image analysis and segmentation. Image s...
Gabor Analysis is frequently used for texture analysis and segmentation. Once the Gaborian feature space is generated it may be interpreted in various ways for image analysis and segmentation. Image s...
We present a novel technique based on a multi-resolutional clustering and nonlinear multi-dimensional scaling of earthquake patterns to investigate observed and synthetic seismic catalogs. The observe...
Techniques for understanding video object motion activity are becoming increasingly important with the widespread adoption of CCTV surveillance systems. Motion trajectories provide rich spatiotemporal...
Recently published gene expression profiles and proteomic mass/charge ratios are extremely high-dimensional data. Though support vector machines can well learn the inner relationship of the data for c...
In speech recognition, the description of the intra-state feature space is an important issue in systems based on HMM-derived acoustic models. The existing techniques include the famous methods based ...

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