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Balanced Mixture of SuperNets for 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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Contribution to journal
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Conference article
›
peer-review
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Keyphrases
Supernet
100%
Downsampling
80%
CIFAR-10
40%
Network Architecture Search
40%
Search Methods
20%
Hyperparameters
20%
Granularity
20%
Convolutional Neural Network Architecture
20%
Weight Sharing
20%
Strided Convolution
20%
CIFAR-100
20%
Weighted Model
20%
Food101
20%
Image Feature Analysis
20%
Optimal Pooling
20%
Receptive Field Size
20%
Computer Science
Network Architecture
100%
Convolutional Neural Network
100%
Neural Network Architecture
50%
Leaning Parameter
50%
image feature
50%
Granularity
50%
Receptive Field
50%
Convolution
50%
Engineering
Convolutional Neural Network
100%
Neural Network Architecture
50%
Granularity
50%
Receptive Field Size
50%
Mathematics
Convolutional Neural Network
100%
Receptive Field
50%
Convolution
50%