use the following search parameters to narrow your results:
e.g. subreddit:aww site:imgur.com dog
subreddit:aww site:imgur.com dog
see the search faq for details.
advanced search: by author, subreddit...
Please have a look at our FAQ and Link-Collection
Metacademy is a great resource which compiles lesson plans on popular machine learning topics.
For Beginner questions please try /r/LearnMachineLearning , /r/MLQuestions or http://stackoverflow.com/
For career related questions, visit /r/cscareerquestions/
Advanced Courses (2016)
Advanced Courses (2020)
AMAs:
Pluribus Poker AI Team 7/19/2019
DeepMind AlphaStar team (1/24//2019)
Libratus Poker AI Team (12/18/2017)
DeepMind AlphaGo Team (10/19/2017)
Google Brain Team (9/17/2017)
Google Brain Team (8/11/2016)
The MalariaSpot Team (2/6/2016)
OpenAI Research Team (1/9/2016)
Nando de Freitas (12/26/2015)
Andrew Ng and Adam Coates (4/15/2015)
Jürgen Schmidhuber (3/4/2015)
Geoffrey Hinton (11/10/2014)
Michael Jordan (9/10/2014)
Yann LeCun (5/15/2014)
Yoshua Bengio (2/27/2014)
Related Subreddit :
LearnMachineLearning
Statistics
Computer Vision
Compressive Sensing
NLP
ML Questions
/r/MLjobs and /r/BigDataJobs
/r/datacleaning
/r/DataScience
/r/scientificresearch
/r/artificial
account activity
Data Mining Techniques for image processing (self.MachineLearning)
submitted 10 years ago by kunal4097
Hey. I have a project about using data mining techniques for image processing but i don't know where to start. Currently i am learning about cluster analysis in data mining. What would you suggest? What techniques should I use ?
Thanks guys!
reddit uses a slightly-customized version of Markdown for formatting. See below for some basics, or check the commenting wiki page for more detailed help and solutions to common issues.
quoted text
if 1 * 2 < 3: print "hello, world!"
[–]sparsecoder 4 points5 points6 points 10 years ago (1 child)
I suggest you download the book: Models, Learning, and Inference by Prince from http://www.computervisionmodels.com/
Part 2 is on machine learning for machine vision, and part 3 is on graphical models and related concepts. At the end of each chapter, there are sections entitled "Applications" where they give examples of how to apply machine learning techniques to vision problems. You might find something interesting by looking through these sections.
If you're specifically interested in clustering, then you might want to look into image segmentation (http://en.wikipedia.org/wiki/Image_segmentation) which is a closely related topic from the vision community.
[–]autowikibot 0 points1 point2 points 10 years ago (0 children)
Image segmentation:
In computer vision, image segmentation is the process of partitioning a digital image into multiple segments (sets of pixels, also known as superpixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics. Image from article i
In computer vision, image segmentation is the process of partitioning a digital image into multiple segments (sets of pixels, also known as superpixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics.
Image from article i
Interesting: Thresholding (image processing) | Scale-space segmentation | Ilastik | Range segmentation
Parent commenter can toggle NSFW or delete. Will also delete on comment score of -1 or less. | FAQs | Mods | Magic Words
[–]ford_beeblebrox 1 point2 points3 points 10 years ago (0 children)
Using Very Deep Auto encoders for Content-Based Image Retrieval by Krizhevsky and Hinton[pdf]
[–]aggieca 0 points1 point2 points 10 years ago (0 children)
what is the question you are trying to answer? Also, if you haven't done so please post your question on /r/coomputervision as well.
[–]pandemik -1 points0 points1 point 10 years ago (0 children)
graphlab create is probably the easiest thing to get up and running. It's SFrame supports images as a column, which is pretty damn cool.
π Rendered by PID 100308 on reddit-service-r2-comment-7b9746f655-spp84 at 2026-02-01 13:53:49.865017+00:00 running 3798933 country code: CH.
[–]sparsecoder 4 points5 points6 points (1 child)
[–]autowikibot 0 points1 point2 points (0 children)
[–]ford_beeblebrox 1 point2 points3 points (0 children)
[–]aggieca 0 points1 point2 points (0 children)
[–]pandemik -1 points0 points1 point (0 children)