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Sladoje, Nataša
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1

Correlated multimodal imaging in life sciences: lessons lea..:

Rudraiah, Pavitra Sokke ; Camacho, Rafael ; Fernandez-Rodriguez, Julia...
Frontiers in Biomaterials Science.  3 (2024)  - p. , 2024
Link: https://doi.org/10.3389/..
 
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2

Deep multiple instance learning versus conventional deep si..:

Koriakina, Nadezhda ; Sladoje, Nataša ; Bašić, Vladimir..
PLOS ONE.  19 (2024)  4 - p. e0302169 , 2024
Link: https://doi.org/10.1371/..
 
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3

INSPIRE: Intensity and spatial information-based deformable..:

Öfverstedt, Johan ; Lindblad, Joakim ; Sladoje, Nataša.
PLOS ONE.  18 (2023)  3 - p. e0282432 , 2023
Link: https://doi.org/10.1371/..
 
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4

Contrastive Learning of Equivariant Image Representations f..:

, In: 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI),
Nordling, Love ; Ofverstedt, Johan ; Lindblad, Joakim. - p. 1-5 , 2023
Link: https://doi.org/10.1109/..
 
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5

Automated detection, segmentation and measurement of major ..:

Kahraman, Ali T. ; Fröding, Tomas ; Toumpanakis, Dimitrios..
Scientific Reports.  13 (2023)  1 - p. , 2023
Link: https://doi.org/10.1038/..
 
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6

Can Representation Learning for Multimodal Image Registrati..:

, In: Pattern Recognition and Image Analysis; Lecture Notes in Computer Science,
Wetzer, Elisabeth ; Lindblad, Joakim ; Sladoje, Nataša - p. 261-275 , 2023
Link: https://doi.org/10.1007/..
 
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7

Guest Editorial: Discrete Geometry and Mathematical Morphol..:

Malmberg, Filip ; Lindblad, Joakim ; Sladoje, Nataša
Journal of Mathematical Imaging and Vision.  64 (2022)  7 - p. 691-692 , 2022
Link: https://doi.org/10.1007/..
 
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8

End-to-end Multiple Instance Learning with Gradient Accumul..:

, In: 2022 IEEE International Conference on Big Data (Big Data),
Andersson, Axel ; Koriakina, Nadezhda ; Sladoje, Natasa. - p. 2742-2746 , 2022
Link: https://doi.org/10.1109/..
 
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9

Introduction:

, In: Bioimage Data Analysis Workflows ‒ Advanced Components and Methods; Learning Materials in Biosciences,
Sladoje, Nataša ; Miura, Kota - p. 1-5 , 2022
Link: https://doi.org/10.1007/..
 
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10

End-to-End Learning and Analysis of Infant Engagement Durin..:

, In: Proceedings of the 2022 International Conference on Multimodal Interaction,
Fraile, Marc ; Fawcett, Christine ; Lindblad, Joakim.. - p. 444-454 , 2022
Link: https://dl.acm.org/doi/1..
 
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11

Cross-Sim-NGF: FFT-Based Global Rigid Multimodal Alignment ..:

, In: Biomedical Image Registration; Lecture Notes in Computer Science,
Öfverstedt, Johan ; Lindblad, Joakim ; Sladoje, Nataša - p. 156-165 , 2022
Link: https://doi.org/10.1007/..
 
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12

Is image-to-image translation the panacea for multimodal im..:

Lu, Jiahao ; Öfverstedt, Johan ; Lindblad, Joakim..
PLOS ONE.  17 (2022)  11 - p. e0276196 , 2022
Link: https://doi.org/10.1371/..
 
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13

Fast computation of mutual information in the frequency dom..:

Öfverstedt, Johan ; Lindblad, Joakim ; Sladoje, Nataša
Pattern Recognition Letters.  159 (2022)  - p. 196-203 , 2022
Link: https://doi.org/10.1016/..
 
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14

Automatic analysis of infant engagement during play: An end..:

, In: Companion Publication of the 2021 International Conference on Multimodal Interaction,
Fraile, Marc ; Lindblad, Joakim ; Fawcett, Christine.. - p. 403-407 , 2021
Link: https://dl.acm.org/doi/1..
 
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15

Discrete Geometry and Mathematical Morphology: First Intern.. 

Image Processing, Computer Vision, Pattern Recognition, and Graphics, 12708
Lindblad, Joakim ; Malmberg, Filip ; Sladoje, Nataša - 1st ed. 2021 . , 2021
Link: https://doi.org/10.1007/..
 
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