Johan Fredin Haslum

According to our database, Johan Fredin Haslum authored at least 7 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Are Natural Domain Foundation Models Useful for Medical Image Classification?

Joana Palés Huix, Adithya Raju Ganeshan, Johan Fredin Haslum, Magnus Söderberg, Christos Matsoukas, Kevin Smith

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Bridging Generalization Gaps in High Content Imaging Through Online Self-Supervised Domain Adaptation.

Johan Fredin Haslum, Christos Matsoukas, Karl-Johan Leuchowius, Kevin Smith

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023

Pretrained ViTs Yield Versatile Representations For Medical Images.

Christos Matsoukas, Johan Fredin Haslum, Magnus Söderberg, Kevin Smith

CoRR, 2023

Metadata-guided Consistency Learning for High Content Images.

Johan Fredin Haslum, Christos Matsoukas, Karl-Johan Leuchowius, Erik Müllers, Kevin Smith

Proceedings of the Medical Imaging with Deep Learning, 2023

2022

What Makes Transfer Learning Work for Medical Images: Feature Reuse & Other Factors.

Christos Matsoukas, Johan Fredin Haslum, Moein Sorkhei, Magnus Söderberg, Kevin Smith

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Is it Time to Replace CNNs with Transformers for Medical Images?

Christos Matsoukas, Johan Fredin Haslum, Magnus Söderberg, Kevin Smith

CoRR, 2021

2020

Adding seemingly uninformative labels helps in low data regimes.

Christos Matsoukas, Albert Bou I Hernandez, Yue Liu, Karin Dembrower, Gisele Miranda, Emir Konuk, Johan Fredin Haslum, Athanasios Zouzos, Peter Lindholm, Fredrik Strand, Kevin Smith

Proceedings of the 37th International Conference on Machine Learning, 2020