3D Convolution

A 3D Convolution is a type of convolution where the kernel slides in 3 dimensions as opposed to 2 dimensions with 2D convolutions. One example use case is medical imaging where a model is constructed using 3D image slices. Additionally video based data has an additional temporal dimension over images making it suitable for this module.

Image: Lung nodule detection based on 3D convolutional neural networks, Fan et al


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Component Type
🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign