Vision

This is an unsupervised learning based lustering web tool that has been used to cluster microstructures in Steel based on their physical properties that have been extracted using classical image processing algorithms. Files can then be uploaded in .xlsx or .csv format. The tool supports five different clustering algorithms in combination with dimensionality reduction.

In this work, we propose using U-net and ACGAN as a learning framework for feature generation of medical images followed by classification to validate the quality of generated features.