Pre-trained 3D ResNet-50

Pre-trained Neural Network Toolbox Model for 3D ResNet-50 Network
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Aggiornato 6 mag 2021

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To transfer the learnable parameters from pre-trained 2D ResNet-50 (ImageNet) to 3D one, we duplicated 2D filters (copying them repeatedly) through the third dimension. This is possible since a video or a 3D image can be converted into a sequence of image slices. In the training process, we expect that the 3D ResNet-50 learns patterns in each frame. This model has 48 million learnable parameters.

simply, call "resnet50TL3Dfun()" function.

Cita come

Ebrahimi, Amir, et al. “Convolutional Neural Networks for Alzheimer’s Disease Detection on MRI Images.” Journal of Medical Imaging, vol. 8, no. 02, SPIE-Intl Soc Optical Eng, Apr. 2021, doi:10.1117/1.jmi.8.2.024503.

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Compatibile con R2019b e release successive
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Versione Pubblicato Note della release
1.0.1

The relevant paper is published.

1.0.0