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搜索结果: 1-15 共查到support vector machines相关记录28条 . 查询时间(0.125 秒)
Seed vigour significantly influences the seed production and plant regeneration performance. The capability of NIR spectroscopy to identify seed vigour across multiple tree species rapidly and cost-ef...
In image processing, algorithms for object classification are typically based around machine learning. From the algorithm developer's perspective, these can involve a considerable amount of effort and...
The accuracy of supervised image classification is highly dependent upon several factors such as the design of training set (sample selection, composition, purity and size), resolution of input imager...
Many data-driven personalized services require that private data of users is scored against a trained machine learning model. In this paper we propose a novel protocol for privacy-preserving classific...
In this study, a land cover classification method based on multi-class Support Vector Machines (SVM) is presented to predict the types of land cover in Miyun area. The obtained backscattered full-wave...
This paper reports on research analysing the potential of Support Vector Machines (SVMs) for mapping vegetation from high spatial resolution Ikonos imagery. The work investigated the utility of SVMs f...
Due to its various negative consequences impervious surface is increasingly recognized as a key issue in assessing the sustainability of land use - particularly in urban environments. In Germany, a re...
Remote sensing techniques have been commonly used to map land cover and land use types. For many applications, users may only be interested in a specific land class in an image such as extracting urba...
A combination of the two remote sensing systems, imaging spectrometry (IS) and Light Detection And Ranging (LiDAR), is well suited to map fuel types, especially within the complex wildland urban inte...
The standard 2-norm SVM is known for its good performance in twoclass classification. In this paper, we consider the 1-norm SVM. We argue that the 1-norm SVM may have some advantage over the standard ...
We present a support vector machines (SVM) rationale suitable for regression and quaternary classification problems that use complex data, exploiting the notions of widely linear estimation and pure c...
We investigate the relation of two fundamental tools in machine learning, that is the support vector machine (SVM) for classification, and the Lasso technique used in regression. We show that the resu...
In this paper we extend support vector machines from reproducing kernel Hilbert spaces into reproducing kernel Banach spaces whose reproducing kernels can be defined on nonsymmetric domains. Using the...
Rockburst possibility prediction is an important activity in many underground openings design and construction as well as mining production. Due to the complex features of rockburst hazard assessment ...

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