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Matthew Blaschko
Matthew Blaschko
KU Leuven
Email confirmado em esat.kuleuven.be - Página inicial
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Fine-grained visual classification of aircraft
S Maji, E Rahtu, J Kannala, M Blaschko, A Vedaldi
arXiv preprint arXiv:1306.5151, 2013
23952013
The Lovász-Softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks
M Berman, A Rannen Triki, MB Blaschko
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
10662018
Beyond sliding windows: Object localization by efficient subwindow search
CH Lampert, MB Blaschko, T Hofmann
2008 IEEE conference on computer vision and pattern recognition, 1-8, 2008
10442008
A discriminatively trained fully connected conditional random field model for blood vessel segmentation in fundus images
JI Orlando, E Prokofyeva, MB Blaschko
IEEE transactions on Biomedical Engineering 64 (1), 16-27, 2016
5432016
Efficient subwindow search: A branch and bound framework for object localization
CH Lampert, MB Blaschko, T Hofmann
IEEE transactions on pattern analysis and machine intelligence 31 (12), 2129 …, 2009
5102009
Learning to localize objects with structured output regression
MB Blaschko, CH Lampert
Computer Vision–ECCV 2008: 10th European Conference on Computer Vision …, 2008
4732008
Encoder based lifelong learning
A Rannen, R Aljundi, MB Blaschko, T Tuytelaars
Proceedings of the IEEE international conference on computer vision, 1320-1328, 2017
4172017
Optimizing the dice score and jaccard index for medical image segmentation: Theory and practice
J Bertels, T Eelbode, M Berman, D Vandermeulen, F Maes, R Bisschops, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
3972019
Optimization for medical image segmentation: theory and practice when evaluating with dice score or jaccard index
T Eelbode, J Bertels, M Berman, D Vandermeulen, F Maes, R Bisschops, ...
IEEE transactions on medical imaging 39 (11), 3679-3690, 2020
3432020
An ensemble deep learning based approach for red lesion detection in fundus images
JI Orlando, E Prokofyeva, M Del Fresno, MB Blaschko
Computer methods and programs in biomedicine 153, 115-127, 2018
3342018
Combining local and global image features for object class recognition
DA Lisin, MA Mattar, MB Blaschko, EG Learned-Miller, MC Benfield
2005 IEEE computer society conference on computer vision and pattern …, 2005
3162005
Metrics reloaded: recommendations for image analysis validation
L Maier-Hein, A Reinke, P Godau, MD Tizabi, F Buettner, E Christodoulou, ...
Nature methods, 1-18, 2024
276*2024
Correlational spectral clustering
MB Blaschko, CH Lampert
2008 IEEE conference on computer vision and pattern recognition, 1-8, 2008
2742008
Unsupervised object discovery: A comparison
T Tuytelaars, CH Lampert, MB Blaschko, W Buntine
International journal of computer vision 88, 284-302, 2010
2582010
Learning a category independent object detection cascade
E Rahtu, J Kannala, M Blaschko
2011 international conference on Computer Vision, 1052-1059, 2011
2212011
Common limitations of image processing metrics: A picture story
A Reinke, MD Tizabi, CH Sudre, M Eisenmann, T Rädsch, M Baumgartner, ...
arXiv preprint arXiv:2104.05642, 2021
212*2021
Convolutional neural network transfer for automated glaucoma identification
JI Orlando, E Prokofyeva, M del Fresno, MB Blaschko
12th international symposium on medical information processing and analysis …, 2017
1662017
Learning fully-connected CRFs for blood vessel segmentation in retinal images
JI Orlando, M Blaschko
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014
1642014
R-gap: Recursive gradient attack on privacy
J Zhu, M Blaschko
International Conference on Learning Representations (ICLR), 2021
1452021
B-test: A non-parametric, low variance kernel two-sample test
W Zaremba, A Gretton, M Blaschko
Advances in neural information processing systems 26, 2013
1442013
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