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Albarqouni, Shadi
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1

LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Da..:

Jiao, Yiping ; van der Laak, Jeroen ; Albarqouni, Shadi...
http://arxiv.org/abs/2301.06304.  , 2023
Link: http://arxiv.org/abs/230..
 
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2

FUTURE-AI: International consensus guideline for trustworth..:

Lekadir, Karim ; Feragen, Aasa ; Fofanah, Abdul Joseph...
http://arxiv.org/abs/2309.12325.  , 2023
Link: http://arxiv.org/abs/230..
 
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3

LVM-Med: Learning Large-Scale Self-Supervised Vision Models..:

Nguyen, Duy M. H ; Nguyen, Hoang ; Diep, Nghiem T...
http://arxiv.org/abs/2306.11925.  , 2023
Link: http://arxiv.org/abs/230..
 
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4

FUTURE-AI: International consensus guideline for trustworth..:

Lekadir, Karim ; Feragen, Aasa ; Fofanah, Abdul Joseph...
https://pure.eur.nl/en/publications/e9cf4c38-eed4-4644-9f39-1cf349472c9f.  , 2023
Link: https://pure.eur.nl/en/p..
 
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5

Anomaly-aware multiple instance learning for rare anemia di..:

Kazeminia, Salome ; Sadafi, Ario ; Makhro, Asya...
http://arxiv.org/abs/2207.01742.  , 2022
Link: http://arxiv.org/abs/220..
 
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6

Virtual embeddings and self-consistency for self-supervised..:

Bdair, Tariq ; Abdelhamid, Hossam ; Navab, Nassir.
http://arxiv.org/abs/2206.06023.  , 2022
Link: http://arxiv.org/abs/220..
 
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7

FLamby: Datasets and Benchmarks for Cross-Silo Federated Le..:

Terrail, Jean Ogier Du ; Ayed, Samy-Safwan ; Cyffers, Edwige...
Apprentissage automatique décentralisé et préservant la vie privée.  , 2022
Link: https://hdl.handle.net/2..
 
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8

Transformer based Models for Unsupervised Anomaly Segmentat..:

Ghorbel, Ahmed ; Aldahdooh, Ahmed ; Albarqouni, Shadi.
http://arxiv.org/abs/2207.02059.  , 2022
Link: http://arxiv.org/abs/220..
 
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9

Joint Self-Supervised Image-Volume Representation Learning ..:

Nguyen, Duy M. H ; Nguyen, Hoang ; Truong, Mai T. N...
http://arxiv.org/abs/2212.01893.  , 2022
Link: http://arxiv.org/abs/221..
 
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10

FLamby: Datasets and Benchmarks for Cross-Silo Federated Le..:

Terrail, Jean Ogier du ; Ayed, Samy-Safwan ; Cyffers, Edwige...
http://arxiv.org/abs/2210.04620.  , 2022
Link: http://arxiv.org/abs/221..
 
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11

FedNorm: Modality-Based Normalization in Federated Learning..:

Bernecker, Tobias ; Peters, Annette ; Schlett, Christopher L...
http://arxiv.org/abs/2205.11096.  , 2022
Link: http://arxiv.org/abs/220..
 
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12

Unsupervised Cross-Domain Feature Extraction for Single Blo..:

Salehi, Raheleh ; Sadafi, Ario ; Gruber, Armin...
http://arxiv.org/abs/2207.00501.  , 2022
Link: http://arxiv.org/abs/220..
 
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13

What can we learn about a generated image corrupting its la..:

Tomczak, Agnieszka ; Gupta, Aarushi ; Ilic, Slobodan..
http://arxiv.org/abs/2210.06257.  , 2022
Link: http://arxiv.org/abs/221..
 
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14

Sickle Cell Disease Severity Prediction from Percoll Gradie..:

Sadafi, Ario ; Makhro, Asya ; Livshits, Leonid...
http://arxiv.org/abs/2109.05372.  , 2021
Link: http://arxiv.org/abs/210..
 
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15

FedDis: Disentangled Federated Learning for Unsupervised Br..:

Bercea, Cosmin I ; Wiestler, Benedikt ; Rueckert, Daniel.
http://arxiv.org/abs/2103.03705.  , 2021
Link: http://arxiv.org/abs/210..
 
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