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Balanced Mixture of SuperNetsfor Learning the CNN Pooling Architecture
Mehraveh Javan Roshtkhari
,
Matthew Toews
,
Marco Pedersoli
École de technologie supérieure
Systems Engineering Department
LIVIA - Imaging, Vision and Artificial Intelligence Laboratory
École de technologie supérieure
Research output
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Conference article
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peer-review
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Keyphrases
CIFAR-10
50%
CIFAR-100
25%
Convolutional Neural Network Architecture
25%
Downsampling
100%
Food101
25%
Granularity
25%
Hyperparameters
25%
Image Feature Analysis
25%
Network Architecture Search
50%
Optimal Pooling
25%
Receptive Field Size
25%
Search Methods
25%
Strided Convolution
25%
Supernet
100%
Weight Sharing
25%
Weighted Model
25%
Computer Science
Convolution
50%
Convolutional Neural Network
100%
Granularity
50%
image feature
50%
Leaning Parameter
50%
Network Architecture
100%
Neural Network Architecture
50%
Receptive Field
50%
Engineering
Convolutional Neural Network
100%
Granularity
50%
Neural Network Architecture
50%
Receptive Field Size
50%
Mathematics
Convolution
50%
Convolutional Neural Network
100%
Receptive Field
50%