Trained by me using https://github.com/soumith/imagenet-multiGPU.torch, achieves 56.7% top1 center crop accuracy on ImageNet validation set. Tested here: https://github.com/szagoruyko/imagenet-validation.torch
Download link: https://yadi.sk/d/uX6id_yZoU8FC (247 MB)
Load as:
| require(tm) | |
| a <- Corpus(DirSource("C:/Users/jgrimes/Desktop/text/"), readerControl = list(language="lat")) | |
| #summary(a) | |
| a <- tm_map(a, function(x) iconv(enc2utf8(x), sub = "byte")) | |
| a <- tm_map(a, removePunctuation) | |
| a <- tm_map(a, removeNumbers) | |
| a <- tm_map(a, stripWhitespace) | |
| a <- tm_map(a, tolower) | |
| a <- tm_map(a, removeWords, stopwords("english")) | |
| a <- tm_map(a, stemDocument, language = "english") |
| # Run this first: | |
| # | |
| # install.packages(c('RSQLite.extfuns', 'ggplot2', 'maps')) | |
| # | |
| library(RSQLite) | |
| library(ggplot2) | |
| library(RSQLite.extfuns) | |
| db = dbConnect( | |
| dbDriver("SQLite") |