Exemplar-based 3D human pose estimation with sparse spectral embedding
Sign Up to like & getrecommendations! Published in 2017 at "Neurocomputing"
DOI: 10.1016/j.neucom.2016.09.137
Abstract: Abstract In exemplar-based approaches, human pose estimation is achieved by retrieving relevant poses with images. Therefore, image description is critical and it is common to extract multiple features to better describe the visual input data.… read more here.
Keywords: human pose; spectral embedding; sparse spectral; exemplar based ... See more keywords
Co-Registration of ex vivo Surgical Histopathology and in vivo T2 weighted MRI of the Prostate via multi-scale spectral embedding representation
Sign Up to like & getrecommendations! Published in 2017 at "Scientific Reports"
DOI: 10.1038/s41598-017-08969-w
Abstract: Multi-modal image co-registration via optimizing mutual information (MI) is based on the assumption that intensity distributions of multi-modal images follow a consistent relationship. However, images with a substantial difference in appearance violate this assumption, thus… read more here.
Keywords: spectral embedding; histopathology; scale spectral; multi modal ... See more keywords
On a two-truths phenomenon in spectral graph clustering
Sign Up to like & getrecommendations! Published in 2019 at "Proceedings of the National Academy of Sciences of the United States of America"
DOI: 10.1073/pnas.1814462116
Abstract: Significance Spectral graph clustering—clustering the vertices of a graph based on their spectral embedding—is of significant current interest, finding applications throughout the sciences. But as with clustering in general, what a particular methodology identifies as… read more here.
Keywords: spectral embedding; spectral graph; two truths; graph clustering ... See more keywords
One-Step Adaptive Spectral Clustering Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2022.3217441
Abstract: Deep spectral clustering is a popular and efficient algorithm in unsupervised learning. However, deep spectral clustering methods are organized into three separate steps: affinity matrix learning, spectral embedding learning, and K-means clustering on spectral embedding.… read more here.
Keywords: spectral embedding; step adaptive; one step; spectral clustering ... See more keywords