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Filipe Condessa
Filipe Condessa
BNY
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Title
Cited by
Cited by
Year
Performance measures for classification systems with rejection
F Condessa, J Kovacevic, J Bioucas-Dias
Pattern Recognition 63, 437-450, 2017
452017
Defending multimodal fusion models against single-source adversaries
K Yang, WY Lin, M Barman, F Condessa, Z Kolter
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
282021
Alternating direction optimization for image segmentation using hidden Markov measure field models
J Bioucas-Dias, F Condessa, J Kovačević
Image Processing: Algorithms and Systems XII 9019, 193-207, 2014
272014
Segmentation and detection of colorectal polyps using local polynomial approximation
F Condessa, J Bioucas-Dias
Image Analysis and Recognition: 9th International Conference, ICIAR 2012 …, 2012
252012
Classification with reject option using contextual information
F Condessa, J Bioucas-Dias, CA Castro, JA Ozolek, J Kovačević
2013 IEEE 10th international symposium on biomedical imaging, 1340-1343, 2013
212013
Supervised hyperspectral image classification with rejection
F Condessa, J Bioucas-Dias, J Kovacevic
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE …, 2016
182016
Convex formulation for multiband image classification with superpixel-based spatial regularization
Y Liu, F Condessa, JM Bioucas-Dias, J Li, P Du, A Plaza
IEEE Transactions on Geoscience and Remote Sensing 56 (5), 2704-2721, 2018
142018
Supervised hyperspectral image segmentation: a convex formulation using hidden fields
F Condessa, J Bioucas-Dias, J Kovacevic
IEEE GRSS Workshop Hyperspectral Image Signal Process: Evol. Remote Sens …, 2014
102014
Robust hyperspectral image classification with rejection fields
F Condessa, J Bioucas-Dias, J Kovacevic
IEEE GRSS Workshop Hyperspectral Image Signal Process: Evol. Remote Sens …, 2015
72015
Image classification with rejection using contextual information
F Condessa, J Bioucas-Dias, C Castro, J Ozolek, J Kovačević
arXiv preprint arXiv:1509.01287, 2015
62015
Method and system for breaking backdoored classifiers through adversarial examples
SUN Mingjie, J Kolter, FJC CONDESSA
US Patent App. 17/035,173, 2022
52022
Convex formulation for hyperspectral image classification with superpixels
Y Liu, F Condessa, J Bioucas-Dias, J Li, A Plaza
2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2016
52016
Detection and classification of human colorectal polyps
FJC Condessa
ST, Lisbon, Portugal, 2011
52011
Provably robust deep generative models
F Condessa, Z Kolter
arXiv preprint arXiv:2004.10608, 2020
42020
SegSALSA-STR: A convex formulation to supervised hyperspectral image segmentation using hidden fields and structure tensor regularization
F Condessa, J Bioucas-Dias, J Kovacevic
IEEE GRSS Workshop Hyperspectral Image Signal Process: Evol. Remote Sens …, 2015
42015
Development and validation of an automated classifier to diagnose acute otitis media in children
N Shaikh, SJ Conway, J Kovačević, F Condessa, TR Shope, MA Haralam, ...
JAMA pediatrics 178 (4), 401-407, 2024
32024
System and method for detecting an adversarial attack
FJC Condessa
US Patent 11,657,153, 2023
32023
You only query once: Effective black box adversarial attacks with minimal repeated queries
D Willmott, AK Sahu, F Sheikholeslami, F Condessa, Z Kolter
arXiv preprint arXiv:2102.00029, 2021
32021
Method and system for low-query black-box universal attacks
DT Willmott, AK Sahu, F Sheikholeslami, FJC CONDESSA, J KOLTER
US Patent 12,026,621, 2024
22024
Leveraging foundation models to improve lightweight clients in federated learning
X Wu, WY Lin, D Willmott, F Condessa, Y Huang, Z Li, MR Ganesh
arXiv preprint arXiv:2311.08479, 2023
22023
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