Skip to content

pythonuser200/Convolutional_Selective_Autoencoder

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

7 Commits
 
 
 
 

Repository files navigation

##################################################################################################

DATA ACCESS FORM:

Please fill out this form that asks for your name, a valid email address and the name of the institution you are affiliated with, to gain access to the data and model weights:

https://docs.google.com/forms/d/1Vnyk03rVDSPlP8lUAD9WVTedKikcS497Cr2qnHsmCz8/edit


Thank you for your interest. The download link will be sent to your email once the form is completed. 

OPTIMIZER USED: Stochastic Gradient Descent (lr = 0.001)
BATCH_SIZE for Training: 128
Epochs = 100

INPUT SHAPE: (16, 16)

GPU Used: NVIDIA GeForce GTX TITAN BLACK (6074 MiB of dedicated GPU memory) 
CUDA 7.5

Training Samples = 59184 (validation split = 0.1)
test Samples = 3200



About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published