This is implementation of AlexNet(2012) with 3D Convolution on TensorFlow (AlexNet 3D).

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Deep Learning AlexNet3D
Overview

AlexNet_3dConv

TensorFlow implementation of AlexNet(2012) by Alex Krizhevsky, with 3D convolutiional layers.

3D AlexNet

3D AlexNet Network with a standart AlexNet architecture, but it has 3D instead 2D filters on each Conv and Pool layers.

Standart AlexNet

Standart AlexNet

To fit this model into memory, model training proccess can be refactored with @OpenAI's Gradient Checkpointing algorithm https://github.com/openai/gradient-checkpointing

  • Note: This model needs a lot of GPU memory. Training session will not starts on 1 GPU without additional data separation or code's parallelization (or https://github.com/openai/gradient-checkpointing for example).

  • Note2: This model doesn't pretend to be the SilverBullet in 3D image recognition (like AlexNet was in 2D). It's just an example of 3D convolutional model in TensorFlow.

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Comments
  • How to organize the data ?

    How to organize the data ?

    Hi, I am new to Python and Numpy. I would like to know how should I prepare the data to use this code please ? What should be the organization of the data inside the array ? In my comprehension, this algorithm allows to classify images of size 227x227x(Z). How could all the images be reshape in a 111x111x111 array ? I suppose I have a wrong comprehension of the code. Thank you very much for any help.

    opened by Aysha9 0
Owner
Denis Timonin
AI Solutions Architect at NVIDIA
Denis Timonin
GitHub
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