This project is an implementation of image analysis techniques inspired by the paper "Multimedia Retrieval through Unsupervised Hypergraph-based Manifold Ranking". The goal is to explore and apply unsupervised hypergraph-based manifold ranking for image retrieval tasks.
Our dataset consisted of images categorized into two classes: cats (label=0) and dogs (label=1).



- D. C. G. Pedronette, L. P. Valem, J. Almeida and R. da S. Torres, "Multimedia Retrieval Through Unsupervised Hypergraph-Based Manifold Ranking." IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. DOI: 10.1109/TIP.2019.2920526.