Gustavo Carneiro
Gustavo Carneiro
Professor, University of Adelaide
Verified email at adelaide.edu.au - Homepage
Title
Cited by
Cited by
Year
Supervised learning of semantic classes for image annotation and retrieval
G Carneiro, AB Chan, PJ Moreno, N Vasconcelos
IEEE transactions on pattern analysis and machine intelligence 29 (3), 394-410, 2007
11512007
Unsupervised cnn for single view depth estimation: Geometry to the rescue
R Garg, VK Bg, G Carneiro, I Reid
European conference on computer vision, 740-756, 2016
8212016
Learning local image descriptors with deep siamese and triplet convolutional networks by minimising global loss functions
V Kumar BG, G Carneiro, I Reid
Proceedings of the IEEE conference on computer vision and pattern …, 2016
2362016
Combining deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance
TA Ngo, Z Lu, G Carneiro
Medical image analysis 35, 159-171, 2017
2092017
Formulating semantic image annotation as a supervised learning problem
G Carneiro, N Vasconcelos
2005 IEEE Computer Society Conference on Computer Vision and Pattern …, 2005
2062005
Detection and measurement of fetal anatomies from ultrasound images using a constrained probabilistic boosting tree
G Carneiro, B Georgescu, S Good, D Comaniciu
IEEE transactions on medical imaging 27 (9), 1342-1355, 2008
2032008
Unregistered multiview mammogram analysis with pre-trained deep learning models
G Carneiro, J Nascimento, AP Bradley
International Conference on Medical Image Computing and Computer-Assisted …, 2015
1982015
Multi-scale phase-based local features
G Carneiro, AD Jepson
2003 IEEE Computer Society Conference on Computer Vision and Pattern …, 2003
1912003
Smart mining for deep metric learning
B Harwood, V Kumar BG, G Carneiro, I Reid, T Drummond
Proceedings of the IEEE International Conference on Computer Vision, 2821-2829, 2017
1662017
Automated mass detection in mammograms using cascaded deep learning and random forests
N Dhungel, G Carneiro, AP Bradley
2015 international conference on digital image computing: techniques and …, 2015
1622015
The segmentation of the left ventricle of the heart from ultrasound data using deep learning architectures and derivative-based search methods
G Carneiro, JC Nascimento, A Freitas
IEEE Transactions on Image Processing 21 (3), 968-982, 2011
1622011
Multi-modal cycle-consistent generalized zero-shot learning
R Felix, I Reid, G Carneiro
Proceedings of the European Conference on Computer Vision (ECCV), 21-37, 2018
1482018
A deep learning approach for the analysis of masses in mammograms with minimal user intervention
N Dhungel, G Carneiro, AP Bradley
Medical image analysis 37, 114-128, 2017
1482017
Robust optimization for deep regression
V Belagiannis, C Rupprecht, G Carneiro, N Navab
Proceedings of the IEEE international conference on computer vision, 2830-2838, 2015
1442015
An improved joint optimization of multiple level set functions for the segmentation of overlapping cervical cells
Z Lu, G Carneiro, AP Bradley
IEEE Transactions on Image Processing 24 (4), 1261-1272, 2015
1422015
Phase-based local features
G Carneiro, AD Jepson
European Conference on Computer Vision, 282-296, 2002
1332002
A bayesian data augmentation approach for learning deep models
T Tran, T Pham, G Carneiro, L Palmer, I Reid
arXiv preprint arXiv:1710.10564, 2017
1192017
Combining multiple dynamic models and deep learning architectures for tracking the left ventricle endocardium in ultrasound data
G Carneiro, JC Nascimento
IEEE transactions on pattern analysis and machine intelligence 35 (11), 2592 …, 2013
1022013
Automated nucleus and cytoplasm segmentation of overlapping cervical cells
Z Lu, G Carneiro, AP Bradley
International Conference on Medical Image Computing and Computer-Assisted …, 2013
1002013
Deep learning and structured prediction for the segmentation of mass in mammograms
N Dhungel, G Carneiro, AP Bradley
International Conference on Medical image computing and computer-assisted …, 2015
972015
The system can't perform the operation now. Try again later.
Articles 1–20