Cikkek nyilvánosan hozzáférhető megbízással - Marcello PelilloTovábbi információ
Sehol sem hozzáférhető: 8
Asymmetric siamese networks for semantic change detection in aerial images
K Yang, GS Xia, Z Liu, B Du, W Yang, M Pelillo, L Zhang
IEEE Transactions on Geoscience and Remote Sensing, 2021
Megbízások: National Natural Science Foundation of China
HELP: An LSTM-based approach to hyperparameter exploration in neural network learning
W Li, WWY Ng, T Wang, M Pelillo, S Kwong
Neurocomputing 442, 161-172, 2021
Megbízások: National Natural Science Foundation of China, Research Grants Council, Hong Kong
LiSSA: localized stochastic sensitive autoencoders
T Wang, WWY Ng, M Pelillo, S Kwong
IEEE Transactions on Cybernetics, 2019
Megbízások: National Natural Science Foundation of China, Research Grants Council, Hong Kong
Towards parameter-free clustering for real-world data
J Hou, H Yuan, M Pelillo
Pattern Recognition 134, 109062, 2023
Megbízások: National Natural Science Foundation of China
Icpr2018 contest on object detection in aerial images (odai-18)
J Ding, Z Zhu, GS Xia, X Bai, S Belongie, J Luo, M Datcu, M Pelillo, ...
2018 24th International Conference on Pattern Recognition (ICPR), 1-6, 2018
Megbízások: National Natural Science Foundation of China
Game-theoretic hypergraph matching with density enhancement
J Hou, H Yuan, M Pelillo
Pattern Recognition 133, 109035, 2023
Megbízások: National Natural Science Foundation of China
A game-theoretic hyper-graph matching algorithm
J Hou, M Pelillo
2018 24th International Conference on Pattern Recognition (ICPR), 1012-1017, 2018
Megbízások: National Natural Science Foundation of China
Hashing-based affinity matrix for dominant set clustering
Q Li, X Tian, WWY Ng, M Pelillo
Neurocomputing 501, 544-554, 2022
Megbízások: National Natural Science Foundation of China
Valahol hozzáférhető: 33
DOTA: A large-scale dataset for object detection in aerial images
GS Xia, X Bai, J Ding, Z Zhu, S Belongie, J Luo, M Datcu, M Pelillo, ...
CVPR 2018 -- IEEE Conference on Computer Vision and Pattern Recognition, 2018
Megbízások: National Natural Science Foundation of China
Object detection in aerial images: A large-scale benchmark and challenges
J Ding, N Xue, GS Xia, X Bai, W Yang, MY Yang, S Belongie, J Luo, ...
IEEE transactions on pattern analysis and machine intelligence 44 (11), 7778 …, 2021
Megbízások: National Natural Science Foundation of China
Structured class-labels in random forests for semantic image labelling
P Kontschieder, S Rota Bulò, H Bischof, M Pelillo
ICCV 2011 -- IEEE International Conference on Computer Vision, 2190-2197, 2011
Megbízások: Austrian Science Fund
Wild patterns reloaded: A survey of machine learning security against training data poisoning
AE Cinà, K Grosse, A Demontis, S Vascon, W Zellinger, BA Moser, ...
ACM Computing Surveys 55 (13s), 1-39, 2023
Megbízások: European Commission, Government of Italy
Probabilistic consensus clustering using evidence accumulation
A Lourenço, SR Bulo, N Rebagliati, ALN Fred, MAT Figueiredo, M Pelillo
Machine Learning 98 (1), 331-357, 2015
Megbízások: Fundação para a Ciência e a Tecnologia, Portugal
Poisoning complete-linkage hierarchical clustering
B Biggio, SR Bulò, I Pillai, M Mura, EZ Mequanint, M Pelillo, F Roli
Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR …, 2014
Megbízások: Government of Italy
A black-box adversarial attack for poisoning clustering
AE Cinà, A Torcinovich, M Pelillo
Pattern Recognition 122, 108306, 2022
Megbízások: Government of Italy
A functional representation for graph matching
FD Wang, N Xue, Y Zhang, GS Xia, M Pelillo
IEEE Transactions on Pattern Analysis and Machine Intelligence 42 (11), 2737 …, 2019
Megbízások: National Natural Science Foundation of China
Deep constrained dominant sets for person re-identification
LT Alemu, M Pelillo, M Shah
ICCV 2019 -- IEEE International Conference on Computer Vision, 9855-9864, 2019
Megbízások: US Department of Defense, US Office of the Director of National Intelligence
Multi-target tracking in multiple non-overlapping cameras using fast-constrained dominant sets
YT Tesfaye, E Zemene, A Prati, M Pelillo, M Shah
International Journal of Computer Vision 127 (9), 1303-1320, 2019
Megbízások: US Department of Defense, US Office of the Director of National Intelligence
Context-sensitive decision forests for object detection
P Kontschieder, SR Bulò, A Criminisi, P Kohli, M Pelillo, H Bischof
NIPS -- Advances in Neural Information Processing Systems, 431-439, 2012
Megbízások: Austrian Science Fund
Locality-aware subgraphs for inductive link prediction in knowledge graphs
HA Mohamed, D Pilutti, S James, A Del Bue, M Pelillo, S Vascon
Pattern Recognition Letters 167, 90-97, 2023
Megbízások: European Commission
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