activity
20132026
most citedDeep Learning for Whole Slide Image Analysis: An Overview

342 citations · 787 across the 44 of their papers we have counts for

collaborators
Showing 2016Show all

6 papers · 1 filter

q-bio.QM2016★ 9 cited

Prediction of future hospital admissions - what is the tradeoff between specificity and accuracy?

Ieva Vasiljeva, Ognjen Arandjelovic

Large amounts of electronic medical records collected by hospitals across the developed world offer unprecedented possibilities for knowledge discovery using computer based data mi…

cs.CL2016

Identification of promising research directions using machine learning aided medical literature analysis

Victor Andrei, Ognjen Arandjelovic

The rapidly expanding corpus of medical research literature presents major challenges in the understanding of previous work, the extraction of maximum information from collected da…

cs.CV2016

Achieving stable subspace clustering by post-processing generic clustering results

Duc-Son Pham, Ognjen Arandjelovic, Svetha Venkatesh

We propose an effective subspace selection scheme as a post-processing step to improve results obtained by sparse subspace clustering (SSC). Our method starts by the computation of…

cs.CV2016★ 4 cited

Learnt quasi-transitive similarity for retrieval from large collections of faces

Ognjen Arandjelovic

We are interested in identity-based retrieval of face sets from large unlabelled collections acquired in uncontrolled environments. Given a baseline algorithm for measuring the sim…

cs.CV2016★ 4 cited

Highly accurate gaze estimation using a consumer RGB-depth sensor

Reza Shoja Ghiass, Ognjen Arandjelovic

Determining the direction in which a person is looking is an important problem in a wide range of HCI applications. In this paper we describe a highly accurate algorithm that perfo…

cs.CV2016

Descriptor transition tables for object retrieval using unconstrained cluttered video acquired using a consumer level handheld mobile device

Warren Rieutort-Louis, Ognjen Arandjelovic

Visual recognition and vision based retrieval of objects from large databases are tasks with a wide spectrum of potential applications. In this paper we propose a novel recognition…