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convolution kernel

Descending Path Convolution Kernel for Syntactic Structures

Descending Path Convolution Kernel for Syntactic Structures

... new kernel over syntactic trees that operates on descending paths through the tree rather than production rules as used in most existing ...tree kernel (Moschitti, 2006), and is less ad hoc than the ...

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Convolution Kernel over Packed Parse Forest

Convolution Kernel over Packed Parse Forest

... forest-based convolution kernel to mine structured features directly from packed ...tree kernel. We evaluate the proposed kernel in two real NLP applications, relation extraction and semantic ...

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Numerical Method for solving Volterra Integral Equations with a Convolution Kernel

Numerical Method for solving Volterra Integral Equations with a Convolution Kernel

... Abstract—This paper presents a numerical method for solv- ing the Volterra integral equation with a convolution kernel. The integral equation was first converted to an algebraic equation using the Laplace ...

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A Convolution Kernel Approach to Identifying Comparisons in Text

A Convolution Kernel Approach to Identifying Comparisons in Text

... SNK’s parameters were optimized to non-trivial cases (S > 1 and L > 1) by the grid-search, i.e., S = 3 and L = 2 for Digital Camera and S = 2 and L = 3 for Cell Phone. The trivial case S = 1 represents a standard ...

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A Hybrid Convolution Tree Kernel for Semantic Role Labeling

A Hybrid Convolution Tree Kernel for Semantic Role Labeling

... Many kernel functions have been proposed in machine learning community and have been ap- plied to NLP ...of convolution kernels, more and more kernels for restricted syntaxes or specific do- mains, such as ...

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Human motor decoding from neural signals: a review

Human motor decoding from neural signals: a review

... as a robust representation for decoding outputs consis- tent with user’s intent. Non-negative matrix factorization (NMF) [140] has been commonly used to extract muscle synergies from multichannel EMG signals for ...

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Identifying High Impact Sub Structures for Convolution Kernels in Document level Sentiment Classification

Identifying High Impact Sub Structures for Convolution Kernels in Document level Sentiment Classification

... Our research builds on previous work in the field of sentiment classification and convolution kernel- s. For sentiment classification, the design of lexi- cal and syntactic features is an important first ...

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Context Sensitive Convolution Tree Kernel for Pronoun Resolution

Context Sensitive Convolution Tree Kernel for Pronoun Resolution

... A convolution kernel (Haussler ...specialized convolution kernel, the convolution tree kernel, proposed in Collins and Duffy (2001), counts the number of common sub- trees ...

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Solvability of some classes of singular integral equations of convolution type via Riemann–Hilbert problem

Solvability of some classes of singular integral equations of convolution type via Riemann–Hilbert problem

... Cauchy kernel and convolution kernel, in which include equations with one or two convolution kernels, equation of Wiener–Hopf type, and dual ...

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Kernels for Sequentially Ordered Data

Kernels for Sequentially Ordered Data

... alignment kernel, see Bahlmann et ...relation-convolution kernel framework, Haussler (1999), the existing literature provides no unifying approach to kernels for sequences: for example the relation ...

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Fine Grained Classification of Product Images Based on Convolutional Neural Networks

Fine Grained Classification of Product Images Based on Convolutional Neural Networks

... With the rapid development of the Internet of things and e-commerce, fea- ture-based image retrieval and classification have become a serious challenge for shoppers searching websites for relevant product information. ...

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A Study of Convolution Tree Kernel with Local Alignment

A Study of Convolution Tree Kernel with Local Alignment

... structural kernel function, Haussler (1999) introduced a general type of kernel function, called“ Convolution ...tree kernel calculation by count- ing the common ...tree kernel to ...

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Human Face Super Resolution Based on Hybrid Algorithm

Human Face Super Resolution Based on Hybrid Algorithm

... deep convolution neural network is improved, the convolution neural network is added to the pool layer, the convolution kernel size is adjusted, the parameters are reduced, and the op- eration ...

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Intelligent Image Acquisition of License Plate Image Using Kernel Estimation Algorithm

Intelligent Image Acquisition of License Plate Image Using Kernel Estimation Algorithm

... blur kernel depends upon the relative motion involving the movement vehicle and fixed surveillance camera during the presentation ...blur kernel of license plate image can be made as a linear of license ...

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Dataset Pre-Processing and Artificial Augmentation, Network Architecture and Training Parameters used in Appropriate Training of Convolutional Neural Networks for Classification Based Computer Vision Applications: A Survey

Dataset Pre-Processing and Artificial Augmentation, Network Architecture and Training Parameters used in Appropriate Training of Convolutional Neural Networks for Classification Based Computer Vision Applications: A Survey

... two convolution layers and two subsampling layers. The convolution layers had 5x5 sized kernels with 6 kernels in the first one and 16 kernels in the ...three convolution layers each with 16 filter ...

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Detection and Recognition of License Number Plate from Fast Moving Vehicle

Detection and Recognition of License Number Plate from Fast Moving Vehicle

... g) Deconvolution method: Deconvolution is an algorithm-based process used to reverse the effects of convolution on recorded data. The concept of deconvolution is widely used in the techniques of signal processing ...

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Simple Attention Based Representation Learning for Ranking Short Social Media Posts

Simple Attention Based Representation Learning for Ranking Short Social Media Posts

... one kernel for the query token ‘Evernote’ is ...the kernel via element-wise product (blue dotted ...the convolution window are used as attention weights in the ...

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Comparison of Digital Image Inpainting Techniques Based on SSIM

Comparison of Digital Image Inpainting Techniques Based on SSIM

... A convolution based technique using bilateral filtering is proposed by ...a convolution with a bilateral averaging ...the kernel function assumes values close to one for pixels on the same side, and ...

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Segmentation of lung field from saliency maps by convolution neural network in chest radiographs using machine learning

Segmentation of lung field from saliency maps by convolution neural network in chest radiographs using machine learning

... We next explain how to convert classification nets into fully convolutional nets that produce coarse output maps. For pixel wise prediction, we need to connect these coarse outputs back to the pixels. Section 3.2 ...

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On spectral properties of the modified convolution operator

On spectral properties of the modified convolution operator

... Remark Since the s-numbers of convolution operator A coincide with the modules of the Fourier coefficients of the kernel K , the problem of estimating the s-numbers of “transformed” operat[r] ...

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