Automatic Crack Detection – with Deep Learning
[This article was first published on R – recurrent null, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
On Friday at DOAG Big Data Days, I presented one possible application of deep learning: using deep learning for automatic crack detection – with some background theory, a Keras model trained from scratch, and the use of VGG16 pretrained on Imagenet. The amount of input data really was minimal, and the resulting accuracy, under these circumstances, not bad at all! Here are the slides.
If you’re interested, I’ll have a webcast on this as part of the Trivadis tricast series (registration). The talk will be in German though, so I guess some working knowledge of German would be helpful 
Thanks for reading!
To leave a comment for the author, please follow the link and comment on their blog: R – recurrent null.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.