Knowledge-guided pretext learning for utero-placental interface detection
Modern machine learning systems, such as convolutional neural networks rely on a rich collection of training data to learn discriminative representations. In many medical imaging applications, unfortunately, collecting a large set of well-annotated data is prohibitively expensive. To overcome data s...
Main Authors: | Qi, H, Collins, S, Noble, JA |
---|---|
Format: | Conference item |
Jezik: | English |
Izdano: |
Springer
2020
|
Podobne knjige/članki
-
SURFACE PARAMETERISATION OF THE UTERO/PLACENTAL INTERFACE USING 3D POWER DOPPLER ULTRASOUND
od: Stevenson, G, et al.
Izdano: (2011) -
UPI-Net: Semantic contour detection in placental ultrasound
od: Qi, H, et al.
Izdano: (2019) -
Pretexting and means to counter it
od: U. A. Mikhaleva
Izdano: (2023-08-01) -
Racially Motivated Spying Pretext
od: Vinay Patel
Izdano: (2021-03-01) -
Donacuige, literature as a pretext
od: Iñaki Tofiño Quesada
Izdano: (2014-09-01)