312 citations · 613 across the 13 of their papers we have counts for
6 papers · 1 filter
Unsupervised domain adaptation in brain lesion segmentation with adversarial networks
Konstantinos Kamnitsas, Christian Baumgartner, Christian Ledig +8
Significant advances have been made towards building accurate automatic segmentation systems for a variety of biomedical applications using machine learning. However, the performan…
Predicting Personal Traits from Facial Images using Convolutional Neural Networks Augmented with Facial Landmark Information
Yoad Lewenberg, Yoram Bachrach, Sukrit Shankar +1
We consider the task of predicting various traits of a person given an image of their face. We estimate both objective traits, such as gender, ethnicity and hair-color; as well as…
Measuring Neural Net Robustness with Constraints
Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos +3
Despite having high accuracy, neural nets have been shown to be susceptible to adversarial examples, where a small perturbation to an input can cause it to become mislabeled. We pr…
Deep Roots: Improving CNN Efficiency with Hierarchical Filter Groups
Yani Ioannou, Duncan Robertson, Roberto Cipolla +1
We propose a new method for creating computationally efficient and compact convolutional neural networks (CNNs) using a novel sparse connection structure that resembles a tree root…
Refining Architectures of Deep Convolutional Neural Networks
Sukrit Shankar, Duncan Robertson, Yani Ioannou +2
Deep Convolutional Neural Networks (CNNs) have recently evinced immense success for various image recognition tasks. However, a question of paramount importance is somewhat unanswe…
Decision Forests, Convolutional Networks and the Models in-Between
Yani Ioannou, Duncan Robertson, Darko Zikic +4
This paper investigates the connections between two state of the art classifiers: decision forests (DFs, including decision jungles) and convolutional neural networks (CNNs). Decis…