In this paper we show how the generation of documents can be thought of as a k-stage Markov process, which leads to a Fisher kernel from which the n-gram and string kernels can be reconstructed. The Fisher kernel view gives a more exible insight into the string kernel and suggests how it can be parametrised in a way that re-ects the statistics of the training corpus. Furthermore, the prob-abili...

Super-resolution (SR) is a technique that produces a high resolution (HR) image via employing a number of low resolution (LR) images from the same scene. One of the degradations that attenuates performance of the SR is the blurriness of the input LR images. In many previous works in the SR, the blurriness of the LR images is assumed to be due to the integral effect of the image sensor of the im...

In this paper, we present classes of kernels for machine learning from a statistics perspective. Indeed, kernels are positive definite functions and thus also covariances. After discussing key properties of kernels, as well as a new formula to construct kernels, we present several important classes of kernels: anisotropic stationary kernels, isotropic stationary kernels, compactly supported ker...

Abstract Bayesian optimization (BO) has been leveraged for guiding autonomous and high-throughput experiments in materials science. However, few have evaluated the efficiency of BO across a broad range experimental domains. In this work, we quantify performance with collection surrogate model acquisition function pairs five diverse systems. By defining acceleration enhancement metrics objective...

Grayscale feature is very effective for degraded character recognition. While many papers focus on different feature extraction algorithms on single character recognition, few deals with the impact of the selected feature on segmentation. For recognition-based segmentation, a good recognition performance on single character may not always have good performance on segmentation. In this paper, tw...

The Loewner framework (LF) in combination with Volterra series (VS) offers a non-intrusive approximation method that is capable of identifying bilinear models from time-domain measurements. This uses harmonic inputs which establish natural way for data acquisition. For the general class nonlinear problems VS representation, growing exponential approach allows derivation generalized kernels, nam...

Only a few works has been done for printed devanagari text in the area of optical character recognition. In this paper there is describing about a simple and fast algorithm for detection of italic and bold character in Devanagari script, without recognition of actual character. Here present an automatic information which tells us about the font type phase in the way of weight and slope. The pro...

A key disadvantage of blendshape animation is the labor-intensive task of sculpting blendshapes with individual expressions for each character. In this paper, we propose a novel system ”Character Transfer”, that automatically sculpts blendshapes with individual expressions by extracting them from training examples; this extraction creates a mapping that drives the sculpting process. Comparing o...

The paper presents a novel type of fuzzy sets, called time-Varying Fuzzy Sets (VFS). These fuzzy sets are based on the Gaussian membership functions, they are depended on the error and they are characterized by the displacement of the kernels to both right and left side of the universe of discourse, the two extremes kernels of the universe are fixed for all time. In this work we focus only on t...

The present investigation for studying correlations and path analysis estimates grain yield contributing characters in maize was carried out at Maize Research Centre Seed Farm, Devihosur eleven characters. Days to 50 per cent tasseling significantly positively correlated with days silking negatively plant height, ear cob length, shelling percentage, hundred weight yield. significant percentage ...