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Two-dimensional image classification using unsupervised learning

Asked by Hyeongcheol Lee on 30 Sep 2019
Latest activity Commented on by Hyeongcheol Lee on 4 Oct 2019
For example, I have one thousand two-dimensional images.
I'd like to classify those images into several groups using unsupervised learning.
But, I couldn't find helpful example or document for this problem.
Is there anyone who can help me with this problem?

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1 Answer

Answer by Raunak Gupta on 3 Oct 2019
 Accepted Answer

Hi,
As per my understanding it is required to cluster the images into several groups using unsupervised learning. I would suggest using trainAutoencoder to learn a network which can generate meaningful features of the images, these features can be extracted from the last layer of encoder. The last layer of encoder is a lower dimensional representation of the image which can be used in kmeans for clustering the features in K groups. This way the images will be classified into several groups but be sure that the clustering is based on some high-level similarities between the images.
For more detailed information you may refer to the research papers available for Unsupervised Clustering.

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Thanks for your suggestion. I will try with trainAutoencoder.

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