All packages

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image.CannyEdges — 0.1.1

Implementation of the Canny Edge Detector for Images

image.ContourDetector — 0.1.1

Implementation of the Unsupervised Smooth Contour Line Detection for Images

image.CornerDetectionF9 — 0.1.0

Find Corners in Digital Images with FAST-9

image.CornerDetectionHarris — 0.1.2

Implementation of the Harris Corner Detection for Images

image.dlib — 0.1.1

Image Processing Functionality using the 'dlib' Package

image.libfacedetection — 0.1

Convolutional Neural Network for Face Detection

image.LineSegmentDetector — 0.1.0

Detect Line Segments in Images

image.Otsu — 0.1

Otsu's Image Segmentation Method

image.textlinedetector — 0.2.3

Segment Images in Text Lines and Words

image2data — 1.0.1

Turn Images into Data Sets

imageData — 0.1-62

Aids in Processing and Plotting Data from a Lemna-Tec Scananalyzer

imagefluency — 0.2.5

Image Statistics Based on Processing Fluency

imagefx — 0.4.1

Extract Features from Images

imager — 1.0.1

Image Processing Library Based on 'CImg'

imagerExtra — 1.3.2

Extra Image Processing Library Based on 'imager'

imageseg — 0.5.0

Deep Learning Models for Image Segmentation

imageviewer — 0.1.0

Simple 'htmlwidgets' Image Viewer with WebGL Brightness/Contrast

imaginator — 1.0.0

Simulate General Insurance Policies and Losses

imagine — 2.1.0

IMAGing engINEs, Tools for Application of Image Filters to Data Matrices

IMak — 2.1.0

Item Maker

imbalance — 1.0.2.1

Preprocessing Algorithms for Imbalanced Datasets

imbalanceDatRel — 0.1.5

Relocated Data Oversampling for Imbalanced Data Classification

imbibe — 0.1.1

A Pipe-Friendly Image Calculator

imcExperiment — 0.99.0

Mass Cytometry S4 Class Structure Pipeline for Images

ImCluster — 0.1.0

Efficiency of Cluster Sampling for Crop Surveys

IMD — 1.2.2

Index of Multiple Deprivation Data for the UK

imdbapi — 0.1.0

Get Movie, Television Data from the 'imdb' Database

IMEC — 0.2.0

Ising Model of Explanatory Coherence

iMediate — 0.5.5

Likelihood Methods for Mediation Analysis

imf.data — 0.1.5

An Interface to IMF (International Monetary Fund) Data JSON API

ImFoR — 0.1.0

Non-Linear Height Diameter Models for Forestry

imgpalr — 0.3.2

Create Color Palettes from Images

imgrec — 0.1.3

An Interface for Image Recognition

imguR — 1.0.3

An Imgur.com API Client Package

ImHD — 0.1.0

Artificial Intelligence Based Machine Learning Algorithms for Height Diameter Relationships of Conifer Trees

IMIFA — 2.2.0

Infinite Mixtures of Infinite Factor Analysers and Related Models

IMIX — 1.1.5

Gaussian Mixture Model for Multi-Omics Data Integration

iml — 0.11.3

Interpretable Machine Learning

IMmailgun — 0.1.2

Send Emails using 'Mailgun'

immcp — 1.0.3

Poly-Pharmacology Toolkit for Traditional Chinese Medicine Research

immer — 1.5-13

Item Response Models for Multiple Ratings

Immigrate — 0.2.1

Iterative Max-Min Entropy Margin-Maximization with Interaction Terms for Feature Selection

ImML — 0.1.5

Machine Learning Algorithms Fitting and Validation for Forestry

immunarch — 0.9.1

Bioinformatics Analysis of T-Cell and B-Cell Immune Repertoires

immuneSIM — 0.8.7

Tunable Simulation of B- And T-Cell Receptor Repertoires

ImNN — 0.1.0

Neural Networks for Predicting Volume of Forest Trees

imola — 0.5.0

CSS Layouts (Grid and Flexbox) Implementation for R/Shiny

IMP — 1.1

Interactive Model Performance Evaluation

imp4p — 1.2

Imputation for Proteomics

IMPACT — 0.1.1

The Impact of Items

ImpactEffectsize — 0.7

Calculation and Visualization of the Impact Effect Size Measure

impactflu — 0.1.0

Quantification of Population-Level Impact of Vaccination

impactr — 0.4.2

Mechanical Loading Prediction Through Accelerometer Data

impimp — 0.3.1

Imprecise Imputation for Statistical Matching

implicitExpansion — 0.1.0

Array Operations for Arrays of Mismatching Sizes

implicitMeasures — 0.2.1

Compute Scores for Different Implicit Measures

implied — 0.5

Convert Between Bookmaker Odds and Probabilities

implyr — 0.5.0

R Interface for Apache Impala

import — 1.3.2

An Import Mechanism for R

ImportanceIndice — 0.0.2

Analyzing Data Through of Percentage of Importance Indice and Its Derivations

importar — 0.1.1

Enables Importing/Loading of Packages or Functions While Creating an Alias for Them

ImportExport — 1.3

Import and Export Data

importinegi — 1.2.1

Download and Manage Open Data from INEGI

imprecise101 — 0.2.2.4

Introduction to Imprecise Probabilities

impressionist.colors — 1.0

Impressionism's Color Palettes

imprinting — 0.1.1

Calculate Birth Year-Specific Probabilities of Immune Imprinting to Influenza

ImpShrinkage — 1.0.0

Improved Shrinkage Estimations for Multiple Linear Regression

imptree — 0.5.1

Classification Trees with Imprecise Probabilities

imputeFin — 0.1.2

Imputation of Financial Time Series with Missing Values and/or Outliers

imputeGeneric — 0.1.0

Ease the Implementation of Imputation Methods

imputeLCMD — 2.1

A Collection of Methods for Left-Censored Missing Data Imputation

ImputeLongiCovs — 0.1.0

Longitudinal Imputation of Categorical Variables via a Joint Transition Model

imputeMulti — 0.8.4

Imputation Methods for Multivariate Multinomial Data

imputeR — 2.2

A General Multivariate Imputation Framework

imputeREE — 0.0.5

Impute Missing Rare Earth Element Data in Zircon

ImputeRobust — 1.3-1

Robust Multiple Imputation with Generalized Additive Models for Location Scale and Shape

imputeTestbench — 3.0.3

Test Bench for the Comparison of Imputation Methods

imputeTS — 3.3

Time Series Missing Value Imputation

iMRMC — 1.2.5

Multi-Reader, Multi-Case Analysis Methods (ROC, Agreement, and Other Metrics)

imsig — 1.1.3

Immune Cell Gene Signatures for Profiling the Microenvironment of Solid Tumours

IMTest — 1.0.0

Information Matrix Test for Generalized Partial Credit Models

ImVol — 0.1.0

Volume Prediction of Trees Using Linear and Nonlinear Allometric Equations

in2extRemes — 1.0-3

Into the extRemes Package

inaparc — 1.2.0

Initialization Algorithms for Partitioning Cluster Analysis

inbreedR — 0.3.3

Analysing Inbreeding Based on Genetic Markers

inca — 0.0.4

Integer Calibration

incase — 0.3.2

Pipe-Friendly Vector Replacement with Case Statements

INCATome — 1.0

Internal Control Analysis of Translatome Studies by Microarrays

IncDTW — 1.1.4.4

Incremental Calculation of Dynamic Time Warping

incgraph — 1.0.1

Incremental Graphlet Counting for Network Optimisation

incidence — 1.7.3

Compute, Handle, Plot and Model Incidence of Dated Events

incidence2 — 2.2.3

Compute, Handle and Plot Incidence of Dated Events

IncidencePrevalence — 0.7.2

Estimate Incidence and Prevalence using the OMOP Common Data Model

incidental — 0.1

Implements Empirical Bayes Incidence Curves

incidentally — 1.0.2

Generates Incidence Matrices and Bipartite Graphs

IncomPair — 0.1.0

Comparison of Means for the Incomplete Paired Data

incR — 2.1.0

Analysis of Incubation Data

inctools — 1.0.15

Incidence Estimation Tools

incubate — 1.2.1

Parametric Time-to-Event Analysis with Variable Incubation Phases

indelmiss — 1.0.10

Insertion Deletion Analysis While Accounting for Possible Missing Data

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