Search results for " normalization"

showing 10 items of 33 documents

Appropriate kernels for Divisive Normalization explained by Wilson-Cowan equations

2018

The interaction between wavelet-like sensors in Divisive Normalization is classically described through Gaussian kernels that decay with spatial distance, angular distance and frequency distance. However, simultaneous explanation of (a) distortion perception in natural image databases and (b) contrast perception of artificial stimuli requires very specific modifications in classical Divisive Normalization. First, the wavelet response has to be high-pass filtered before the Gaussian interaction is applied. Then, distinct weights per subband are also required after the Gaussian interaction. In summary, the classical Gaussian kernel has to be left- and right-multiplied by two extra diagonal ma…

Computational NeuroscienceWilson-Cowan modelQuantitative Biology::Neurons and CognitionDivisive Normalization modelFOS: Biological sciencesQuantitative Biology - Neurons and CognitionInteractions in V1Neurons and Cognition (q-bio.NC)
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Co-citation Percentile Rank and JYUcite : a new network-standardized output-level citation influence metric and its implementation using Dimensions A…

2022

AbstractJudging value of scholarly outputs quantitatively remains a difficult but unavoidable challenge. Most of the proposed solutions suffer from three fundamental shortcomings: they involve (i) the concept of journal, in one way or another, (ii) calculating arithmetic averages from extremely skewed distributions, and (iii) binning data by calendar year. Here, we introduce a new metric Co-citation Percentile Rank (CPR), that relates the current citation rate of the target output taken at resolution of days since first citable, to the distribution of current citation rates of outputs in its co-citation set, as its percentile rank in that set. We explore some of its properties with an examp…

Computer scienceValue (computer science)General Social SciencesviiteanalyysiResolution (logic)Library and Information Sciencescomputer.software_genreCo-citationComputer Science ApplicationsSet (abstract data type)Percentile rankcitation count normalizationMetric (mathematics)Data miningarticle-level metricsCitationcomputerarviointitieteellinen julkaisutoimintabibliometriikka
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Histidine-rich glycoprotein-induced vascular normalization improves EPR-mediated drug targeting to and into tumors

2018

Tumors are characterized by leaky blood vessels, and by an abnormal and heterogeneous vascular network. These pathophysiological characteristics contribute to the enhanced permeability and retention (EPR) effect, which is one of the key rationales for developing tumor-targeted drug delivery systems. Vessel abnormality and heterogeneity, however, which typically result from excessive pro-angiogenic signaling, can also hinder efficient drug delivery to and into tumors. Using histidine-rich glycoprotein (HRG) knockout and wild type mice, and HRG-overexpressing and normal t241 fibrosarcoma cells, we evaluated the effect of genetically induced and macrophage-mediated vascular normalization on th…

Histidine-rich glycoproteinUT-Hybrid-DPharmaceutical ScienceVascular normalization02 engineering and technologyPermeabilityArticleMice03 medical and health scienceschemistry.chemical_compoundDrug Delivery Systems0302 clinical medicinePolymethacrylic AcidsCell Line TumorNeoplasmsmedicineAnimalsMethacrylamideTissue DistributionpHPMAFibrosarcomaMice Knockoutchemistry.chemical_classificationDrug CarriersProteins021001 nanoscience & nanotechnologymedicine.diseasePathophysiologyUp-RegulationMice Inbred C57BLHRGNanomedicineTumor targetingchemistryTargeted drug deliveryPermeability (electromagnetism)030220 oncology & carcinogenesisDrug deliveryDrug deliveryCancer researchEPR0210 nano-technologyGlycoprotein
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Multi-Path U-Net Architecture for Cell and Colony-Forming Unit Image Segmentation

2022

U-Net is the most cited and widely-used deep learning model for biomedical image segmentation. In this paper, we propose a new enhanced version of a ubiquitous U-Net architecture, which improves upon the original one in terms of generalization capabilities, while addressing several immanent shortcomings, such as constrained resolution and non-resilient receptive fields of the main pathway. Our novel multi-path architecture introduces a notion of an individual receptive field pathway, which is merged with other pathways at the bottom-most layer by concatenation and subsequent application of Layer Normalization and Spatial Dropout, which can improve generalization performance for small datase…

Layer Normalizationneural networkChemical technologyStem CellsTP1-1185U-NetBiochemistryencoder–decoderAtomic and Molecular Physics and OpticsAnalytical Chemistryskip-connectionsImage Processing Computer-AssistedNeural Networks ComputerU-Net; skip-connections; neural network; encoder–decoder; Layer NormalizationElectrical and Electronic EngineeringInstrumentationSensors; Volume 22; Issue 3; Pages: 990
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Triplet 12B-12C-12N : Search for States with Halo

2020

Previously in [1] neutron halo was confirmed for the 2¯, 1.67 MeV and 1¯, 2.62 MeV states in 12B on base of Asymptotic Normalization Coefficients (ANC) method analysis of the obtained experimental data. An unexpected result was received for the unbound 3¯, 3.39 MeV state. Its halo radius was found to be increased and equal to ~5.9 fm. This result can be considered as an evidence of the halo-like structure in this 12B state. It should be noted that last neutron in this state has a non-zero orbital momentum (l = 2). So question arises about possible existence of states with halo in other members of the isobaric triplet 12B–12C–12N. We can expect the formation of a proton halo in the 2¯, 1.19 …

MDM modelNuclear Theoryasymptotic normalization coefficients neutron and proton haloradii of excited statesNuclear Experiment
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Removing Batch Effects from Longitudinal Gene Expression - Quantile Normalization Plus ComBat as Best Approach for Microarray Transcriptome Data

2016

International audience; Technical variation plays an important role in microarray-based gene expression studies, and batch effects explain a large proportion of this noise. It is therefore mandatory to eliminate technical variation while maintaining biological variability. Several strategies have been proposed for the removal of batch effects, although they have not been evaluated in large-scale longitudinal gene expression data. In this study, we aimed at identifying a suitable method for batch effect removal in a large study of microarray-based longitudinal gene expression. Monocytic gene expression was measured in 1092 participants of the Gutenberg Health Study at baseline and 5-year fol…

Male0301 basic medicineMolecular biologyMicroarrayslcsh:MedicineGene ExpressionPolynomialsMonocytesMathematical and Statistical Techniques0302 clinical medicineLongitudinal StudiesProspective Studieslcsh:ScienceOligonucleotide Array Sequence AnalysisGeneticsPrincipal Component Analysis[SDV.MHEP] Life Sciences [q-bio]/Human health and pathologyMultidisciplinaryGenomicsReplicateMiddle AgedRegressionRNA isolationBioassays and Physiological Analysis030220 oncology & carcinogenesisPhysical SciencesPrincipal component analysisFemaleRNA hybridizationDNA microarrayTranscriptome AnalysisStatistics (Mathematics)Research ArticleAdultComputational biologyBiologyBiomolecular isolationGeneralized linear mixed model03 medical and health sciencesDeming regressionExtraction techniquesGeneticsHumansStatistical MethodsAgedQuantile normalizationMolecular probe techniquesGene Expression Profilinglcsh:RBiology and Life SciencesComputational BiologyGenome AnalysisProbe hybridizationRNA extractionResearch and analysis methodsGene expression profilingMolecular biology techniquesAlgebra030104 developmental biologyNonlinear DynamicsMultivariate Analysislcsh:QMathematics[SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
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Evaluation of Deep Neural Networks for Semantic Segmentation of Prostate in T2W MRI

2020

In this paper, we present an evaluation of four encoder&ndash

MaleSimilarity (geometry)Computer scienceSegNet02 engineering and technologylcsh:Chemical technologyBiochemistryArticleencoder–decoder030218 nuclear medicine & medical imagingAnalytical Chemistry03 medical and health sciencesProstate cancer0302 clinical medicineProstateImage Processing Computer-Assisted0202 electrical engineering electronic engineering information engineeringmedicineHumanslcsh:TP1-1185SegmentationElectrical and Electronic EngineeringInstrumentationmedicine.diagnostic_testPixelbusiness.industryProstateCNNsPattern recognitionMagnetic resonance imagingFCNmedicine.diseaseMagnetic Resonance ImagingU-NetAtomic and Molecular Physics and OpticsSemanticsIntensity normalizationmedicine.anatomical_structureDeepLabV3+Deep neural networks020201 artificial intelligence & image processingNeural Networks ComputerArtificial intelligencebusinessDNNSensors
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How do normalization schemes affect net spillovers? A replication of the Diebold and Yilmaz (2012) study

2019

Abstract This paper replicates the Diebold and Yilmaz (2012) study on the connectedness of the commodity market and three other financial markets: the stock market, the bond market, and the FX market, based on the Generalized Forecast Error Variance Decomposition, GEFVD. We show that the net spillover indices (of directional connectedness), used to assess the net contribution of one market to overall risk in the system, are sensitive to the normalization scheme applied to the GEFVD. We show that, considering data generating processes characterized by different degrees of persistence and covariance, a scalar-based normalization of the Generalized Forecast Error Variance Decomposition is pref…

Normalization (statistics)Economics and EconometricsSocial connectedness020209 energySettore SECS-P/05 - Econometria02 engineering and technologyNormalization schemeconnectednessSpillover effect0502 economics and business0202 electrical engineering electronic engineering information engineeringEconometrics050207 economicsMathematicsspillover normalization connectednessVector autoregression models05 social sciencesFinancial marketCovarianceCausalitySpilloverGeneral EnergynormalizationGeneralized forecast error variance decompositionCommodity price fluctuations Driving forces Nonparametric additive regression modelsVariance decomposition of forecast errorsBond marketStock marketSimulationNormalization schemes
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Visual information flow in Wilson-Cowan networks.

2020

In this paper, we study the communication efficiency of a psychophysically tuned cascade of Wilson-Cowan and divisive normalization layers that simulate the retina-V1 pathway. This is the first analysis of Wilson-Cowan networks in terms of multivariate total correlation. The parameters of the cortical model have been derived through the relation between the steady state of the Wilson-Cowan model and the divisive normalization model. The communication efficiency has been analyzed in two ways: First, we provide an analytical expression for the reduction of the total correlation among the responses of a V1-like population after the application of the Wilson-Cowan interaction. Second, we empiri…

Normalization (statistics)PhysiologyComputer scienceComputationPopulationModels Biological050105 experimental psychologyRetina03 medical and health sciencesWilson–Cowan equations0302 clinical medicineMulti-informationtotal correlationHumans0501 psychology and cognitive sciencesVisual PathwaysEfficient coding hypothesisEfficient representation principleeducationVisual Cortexeducation.field_of_studyNormalization modelGeneral Neuroscience05 social sciencesUnivariateFOS: Biological sciencesQuantitative Biology - Neurons and CognitionDivisive normalizationVisual PerceptionNeurons and Cognition (q-bio.NC)Total correlationNeural Networks ComputerNerve NetAlgorithm030217 neurology & neurosurgeryImage compressionJournal of neurophysiology
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How to standardize (if you must)

2017

In many situations we are interested in appraising the value of a certain characteristic for a given individual relative to the context in which this value is observed. In recent years this problem has become prominent in the evaluation of scientific productivity and impact. A popular approach to such relative valuations consists in using percentile ranks. This is a purely ordinal method that may sometimes lead to counterintuitive appraisals, in that it discards all information about the distance between the raw values within a given context. By contrast, this information is partly preserved by using standardization, i.e., by transforming the absolute values in such a way that, within the s…

Normalization (statistics)z-scoreLocation statisticsStandardizationMonotonic functionLibrary and Information Sciences050905 science studiesSocial Sciences (all)NOPercentile rankCitation analysisEconometricsMathematicsCitation analysis; Dispersion statistics; Location statistics; m-score; Normalization; Standardization; z-score; Social Sciences (all); Computer Science Applications1707 Computer Vision and Pattern Recognition; Library and Information Sciences05 social sciencesCounterintuitiveGeneral Social SciencesLocation statisticDispersion statisticsComputer Science Applications1707 Computer Vision and Pattern RecognitionStandardizationComputer Science Applicationsm-scoreNormalizationConceptual frameworkCitation analysisCitation analysiNormative0509 other social sciences050904 information & library sciencesDispersion statistic
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