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from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation, Flatten
from keras.layers.convolutional import Convolution2D, MaxPooling2D
from keras.layers.normalization import BatchNormalization
#AlexNet with batch normalization in Keras
#input image is 224x224
model = Sequential()
model.add(Convolution2D(64, 3, 11, 11, border_mode='full'))
@bis-carbon
bis-carbon / mnist_siamese_graph.py
Created February 8, 2017 00:40 — forked from mmmikael/mnist_siamese_graph.py
Keras example for siamese training on mnist with graph model
from __future__ import absolute_import
from __future__ import print_function
import numpy as np
np.random.seed(1337) # for reproducibility
import random
from keras.datasets import mnist
from keras.models import Sequential, Graph
from keras.layers.core import *
from keras.optimizers import SGD, RMSprop
@bis-carbon
bis-carbon / mnist_siamese_graph.py
Created February 8, 2017 00:40 — forked from mmmikael/mnist_siamese_graph.py
Keras example for siamese training on mnist with graph model
from __future__ import absolute_import
from __future__ import print_function
import numpy as np
np.random.seed(1337) # for reproducibility
import random
from keras.datasets import mnist
from keras.models import Sequential, Graph
from keras.layers.core import *
from keras.optimizers import SGD, RMSprop