Incremental learning of fetal heart anatomies using interpretable saliency maps
While medical image analysis has seen extensive use of deep neural networks, learning over multiple tasks is a challenge for connectionist networks due to tendencies of degradation in performance over old tasks while adapting to novel tasks. It is pertinent that adaptations to new data distributions...
Hauptverfasser: | Patra, A, Noble, JA |
---|---|
Format: | Conference item |
Sprache: | English |
Veröffentlicht: |
Springer
2020
|
Ähnliche Einträge
Ähnliche Einträge
-
Hierarchical class incremental learning of anatomical structures in fetal echocardiography videos
von: Noble, JA, et al.
Veröffentlicht: (2020) -
Multi-anatomy localization in fetal echocardiography videos
von: Patra, A, et al.
Veröffentlicht: (2019) -
Learning spatio-temporal aggregation for fetal heart analysis in ultrasound video
von: Patra, A, et al.
Veröffentlicht: (2017) -
Anatomy-aware contrastive representation learning for fetal ultrasound
von: Fu, Z, et al.
Veröffentlicht: (2023) -
Anatomy of the normal fetal heart: The basis for understanding fetal echocardiography
von: Beatriz Picazo-Angelin, et al.
Veröffentlicht: (2018-01-01)