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Johan Fredin Haslum
Johan Fredin Haslum
PhD Student, Machine Learning, KTH - Royal Institute of Technology
在 kth.se 的电子邮件经过验证
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Is it time to replace cnns with transformers for medical images?
C Matsoukas, JF Haslum, M Söderberg, K Smith
arXiv preprint arXiv:2108.09038, 2021
1742021
What makes transfer learning work for medical images: Feature reuse & other factors
C Matsoukas, JF Haslum, M Sorkhei, M Söderberg, K Smith
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
832022
Adding seemingly uninformative labels helps in low data regimes
C Matsoukas, AB Hernandez, Y Liu, K Dembrower, G Miranda, E Konuk, ...
International Conference on Machine Learning, 6775-6784, 2020
182020
Pretrained ViTs yield versatile representations for medical images
C Matsoukas, JF Haslum, M Söderberg, K Smith
arXiv preprint arXiv:2303.07034, 2023
13*2023
Are Natural Domain Foundation Models Useful for Medical Image Classification?
JP Huix, AR Ganeshan, JF Haslum, M Söderberg, C Matsoukas, K Smith
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024
122024
Cell Painting-based bioactivity prediction boosts high-throughput screening hit-rates and compound diversity
J Fredin Haslum, CH Lardeau, J Karlsson, R Turkki, KJ Leuchowius, ...
Nature Communications 15 (1), 3470, 2024
52024
Metadata-guided consistency learning for high content images
JF Haslum, C Matsoukas, KJ Leuchowius, E Müllers, K Smith
Medical Imaging with Deep Learning, 918-936, 2024
52024
Is it time to replace CNNs with transformers for medical images?(2021)
C Matsoukas, JF Haslum, M Söderberg, K Smith
arXiv preprint arXiv:2108.09038, 0
5
Bridging generalization gaps in high content imaging through online self-supervised domain adaptation
JF Haslum, C Matsoukas, KJ Leuchowius, K Smith
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024
22024
Machine Learning Methods for Image-based Phenotypic Profiling in Early Drug Discovery
J Fredin Haslum
KTH Royal Institute of Technology, 2024
2024
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