most citedActive Learning from Positive and Unlabeled Data

29 citations · 37 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2018

Bound and Conquer: Improving Triangulation by Enforcing Consistency

Adam Scholefield, Alireza Ghasemi, Martin Vetterli

We study the accuracy of triangulation in multi-camera systems with respect to the number of cameras. We show that, under certain conditions, the optimal achievable reconstruction…

cs.CV2016

On the Accuracy of Point Localisation in a Circular Camera-Array

Alireza Ghasemi, Adam Scholefield, Martin Vetterli

Although many advances have been made in light-field and camera-array image processing, there is still a lack of thorough analysis of the localisation accuracy of different multi-c…

cs.CV2016

SHAPE: Linear-Time Camera Pose Estimation With Quadratic Error-Decay

Alireza Ghasemi, Adam Scholefield, Martin Vetterli

We propose a novel camera pose estimation or perspective-n-point (PnP) algorithm, based on the idea of consistency regions and half-space intersections. Our algorithm has linear ti…

cs.LG2016★ 8 cited

A Bayesian Approach to the Data Description Problem

Alireza Ghasemi, Hamid R. Rabiee, Mohammad T. Manzuri +1

In this paper, we address the problem of data description using a Bayesian framework. The goal of data description is to draw a boundary around objects of a certain class of intere…

cs.LG2016★ 29 cited

Active Learning from Positive and Unlabeled Data

Alireza Ghasemi, Hamid R. Rabiee, Mohsen Fadaee +2

During recent years, active learning has evolved into a popular paradigm for utilizing user's feedback to improve accuracy of learning algorithms. Active learning works by selectin…