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71.
72.
Single image super resolution (SISR) is an important research content in the
field of computer vision and image processing. With the rapid development of deep
neural networks, different image super-resolution models have emerged. Compared to
some traditional SISR methods, deep learning-based methods can complete the superresolution tasks through a single image. In addition, compared with the SISR methods
using traditional convolutional neural networks, SISR based on generative adversarial
networks (GAN) has achieved the most advanced visual performance. In this review, we
first explore the challenges faced by SISR and introduce some common datasets and
evaluation metrics. Then, we review the improved network structures and loss functions
of GAN-based perceptual SISR. Subsequently, the advantages and disadvantages of
different networks are analyzed by multiple comparative experiments. Finally, we
summarize the paper and look forward to the future development trends of GAN-based
perceptual SISR. 相似文献
73.
This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning
of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed
Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given
visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample
size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive
experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr
and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood
(ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given
sparse data, while CL-AIC should be chosen given moderate or large data sample sizes. 相似文献
74.
The standardization data for the California Verbal Learning Test-Second Edition (CVLT-II; D. C. Delis, J. H. Kramer, E. Kaplan, & B. A. Ober, 2000) were used to evaluate the base rate of 6 specific discrepancies between various key variables. The results indicated that CVLT-II performance discrepancies should equal or exceed 1 or 1.5 z score points (depending on the individual comparison) in the hypothesized direction to be considered potentially unusual. However, because about 1 in 3 persons in the standardization sample displayed at least 1 such large discrepancy, it is concluded that these base rates should be viewed only as a starting point for interpretation. (PsycINFO Database Record (c) 2010 APA, all rights reserved) 相似文献
75.
76.
Three-dimensional models, or pharmacophores, describing Euclidean constraints on the location on small molecules of functional
groups (like hydrophobic groups, hydrogen acceptors and donors, etc.), are often used in drug design to describe the medicinal
activity of potential drugs (or ‘ligands’). This medicinal activity is produced by interaction of the functional groups on
the ligand with a binding site on a target protein. In identifying structure-activity relations of this kind there are three
principal issues: (1) It is often difficult to “align” the ligands in order to identify common structural properties that
may be responsible for activity; (2) Ligands in solution can adopt different shapes (or `conformations’) arising from torsional
rotations about bonds. The 3-D molecular substructure is typically sought on one or more low-energy conformers; and (3) Pharmacophore
models must, ideally, predict medicinal activity on some quantitative scale. It has been shown that the logical representation
adopted by Inductive Logic Programming (ILP) naturally resolves many of the difficulties associated with the alignment and
multi-conformation issues. However, the predictions of models constructed by ILP have hitherto only been nominal, predicting
medicinal activity to be present or absent. In this paper, we investigate the construction of two kinds of quantitative pharmacophoric
models with ILP: (a) Models that predict the probability that a ligand is “active”; and (b) Models that predict the actual
medicinal activity of a ligand. Quantitative predictions are obtained by the utilising the following statistical procedures
as background knowledge: logistic regression and naive Bayes, for probability prediction; linear and kernel regression, for
activity prediction. The multi-conformation issue and, more generally, the relational representation used by ILP results in
some special difficulties in the use of any statistical procedure. We present the principal issues and some solutions. Specifically,
using data on the inhibition of the protease Thermolysin, we demonstrate that it is possible for an ILP program to construct
good quantitative structure-activity models. We also comment on the relationship of this work to other recent developments
in statistical relational learning.
Editors: Tamás Horváth and Akihiro Yamamoto 相似文献
77.
织金电视台通过对有线电视网络进行双向改造,为Internet宽带接入、数字电视、VOD等多媒体应用提供了运行平台,介绍织金县城区HFC双向网络设计方案。 相似文献
78.
Masters Rich S. W.; MacMahon Ken M. A.; Pall Hardev S. 《Canadian Metallurgical Quarterly》2004,49(1):79
Objective: This study examined whether disruption of performance is moderated in Parkinson's disease (PD) patients who acquire their motor behaviors in an implicit manner. Method: Twenty-seven patients with PD learned a hammering task in errorless (implicit) or errorful (explicit) conditions and were tested for robustness of motor performance under a secondary task load, which required them to continuously count backward as they performed the hammering task. Results: Patients in the errorless (implicit) motor learning condition exhibited robustness to secondary task loading, whereas patients in the errorful (explicit) motor learning condition did not. Conclusions: Implicit motor learning techniques should be considered by PD rehabilitation specialists in cases in which existing disruption to movements is exacerbated by conscious control. (PsycINFO Database Record (c) 2010 APA, all rights reserved) 相似文献
79.
Rats exposed to a footshock show conditional fear when reexposed to the shock context. Immediate presentation of shock after placement in the context significantly reduces this fear. Preexposure to the context in the absence of shock, coupled with a minimum preshock interval during training, overcomes this immediate shock deficit. Because rats learn about the context during preexposure and express that learning after being reinforced, the context preexposure effect is an aversive analogue of latent learning. The authors examined the effect of the N-methyl-D-aspartate (NMDA) receptor antagonist D,L-2-amino-5-phosphovalerate (APV) on the facilitatory effect of context preexposure. Rats were preexposed to a chamber after APV administration. The next day they were placed in the same chamber without drug and received shock 35 s later. APV blocked the facilitatory effect of preexposure. Therefore NMDA receptors are important for contextual latent learning. (PsycINFO Database Record (c) 2010 APA, all rights reserved) 相似文献
80.
基于支持向量机的多类分类研究 总被引:1,自引:0,他引:1
现今流行的分类方法的重要基础是传统的统计学,前提是要有足够的样本,当样本数目有限时容易出现过学习的问题,导致分类效果不理想。引入支持向量机方法,它基于统计学习理论,采用了结构风险最小化原则代替经验风险最小化原则,较好的解决了小样本学习的问题;又由于采用了核函数思想,把非线性空间的问题转换到线性空间,降低了算法的复杂度。对其相关内容包括优化算法及多类分类问题的解决进行了研究,最后用一个实例说明了该方法的可行性和有效性。 相似文献