
On a Quick Way to Extract Concise Image Descriptors from CNN Models - starkd
http://blog.phash.org/posts/concise-image-descriptor
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TTPrograms
Watch out with your eigenvalue analysis - your covariance matrix is limited to
rank 500 because you're only using 500 images. Furthermore, the smaller
eigenvalues will have eigenvectors with high variance due to the random image
sample (ie. "noisy"). If the singular values start to fall off within ~1-3x of
your sample size then that's indication you need larger sample - eg. random
matrix spectra will still exhibit rolloff in spectra.

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starkd
Thanks. The sample size was limited for memory restrictions. I obtained
similar results in eigenvalues for different random selections of 500 images,
but no doubt a covariance matrix based on more images might tell us more.

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eurticket
Would love to know some results

