activity
20172021
most citedSparse-then-Dense Alignment based 3D Map Reconstruction Method for Endoscopic Capsule Robots

36 citations · 57 across the 4 of their papers we have counts for

collaborators

5 papers

eess.SP2021

Variance reduction in stochastic methods for large-scale regularised least-squares problems

Yusuf Pilavcı, Pierre-Olivier Amblard, Simon Barthelmé +1

Large dimensional least-squares and regularised least-squares problems are expensive to solve. There exist many approximate techniques, some deterministic (like conjugate gradient)…

cs.LG20191 cited

Spectral Graph Wavelet Transform as Feature Extractor for Machine Learning in Neuroimaging

Yusuf Pilavci, Nicolas Farrugia

Graph Signal Processing has become a very useful framework for signal operations and representations defined on irregular domains. Exploiting transformations that are defined on gr…

cs.DM2019

Smoothing graph signals via random spanning forests

Yusuf Y. Pilavci, Pierre-Olivier Amblard, Simon Barthelmé +1

Another facet of the elegant link between random processes on graphs and Laplacian-based numerical linear algebra is uncovered: based on random spanning forests, novel Monte-Carlo…

cs.CV201736 cited

Sparse-then-Dense Alignment based 3D Map Reconstruction Method for Endoscopic Capsule Robots

Mehmet Turan, Yusuf Yigit Pilavci, Ipek Ganiyusufoglu +3

Since the development of capsule endoscopcy technology, substantial progress were made in converting passive capsule endoscopes to robotic active capsule endoscopes which can be co…

cs.CV201720 cited

A fully dense and globally consistent 3D map reconstruction approach for GI tract to enhance therapeutic relevance of the endoscopic capsule robot

Mehmet Turan, Yusuf Yigit Pilavci, Redhwan Jamiruddin +3

In the gastrointestinal (GI) tract endoscopy field, ingestible wireless capsule endoscopy is emerging as a novel, minimally invasive diagnostic technology for inspection of the GI…