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Found 5 papers, 2 papers with code
The Impact of Changes in Resolution on the Persistent Homology of Images
Digital images enable quantitative analysis of material properties at micro and macro length scales, but choosing an appropriate resolution when acquiring the image is challenging.
Persistent Homology with Improved Locality Information for more Effective Delineation
Persistent Homology (PH) has been successfully used to train networks to detect curvilinear structures and to improve the topological quality of their results.
Localized Persistent Homologies for more Effective Deep Learning
Persistent Homologies have been successfully used to increase the performance of deep networks trained to detect curvilinear structures and to improve the topological quality of the results.
Duality in Persistent Homology of Images
We derive the relationship between the persistent homology barcodes of two dual filtered CW complexes.
A Topological "Reading" Lesson: Classification of MNIST using TDA
We present a way to use Topological Data Analysis (TDA) for machine learning tasks on grayscale images.
