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vgg16 architecture

Pouty Parrot answered on June 1, 2021 Popularity 9/10 Helpfulness 2/10

answer vgg16 architecture

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vgg16 architecture

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model = Sequential()

# L1-2
model.add(Conv2D(input_shape=(224, 224, 3), filters=64,kernel_size=(3,3),padding="same", activation="relu"))
model.add(Conv2D(filters=64,kernel_size=(3,3),padding="same", activation="relu"))
model.add(MaxPooling2D(pool_size=(2,2),strides=(2,2)))

# L3-4
model.add(Conv2D(filters=128, kernel_size=(3,3), padding="same", activation="relu"))
model.add(Conv2D(filters=128, kernel_size=(3,3), padding="same", activation="relu"))
model.add(MaxPooling2D(pool_size=(2,2),strides=(2,2)))

# L5-7
model.add(Conv2D(filters=256, kernel_size=(3,3), padding="same", activation="relu"))
model.add(Conv2D(filters=256, kernel_size=(3,3), padding="same", activation="relu"))
model.add(Conv2D(filters=256, kernel_size=(3,3), padding="same", activation="relu"))
model.add(MaxPooling2D(pool_size=(2,2),strides=(2,2)))

# L8-10
model.add(Conv2D(filters=512, kernel_size=(3,3), padding="same", activation="relu"))
model.add(Conv2D(filters=512, kernel_size=(3,3), padding="same", activation="relu"))
model.add(Conv2D(filters=512, kernel_size=(3,3), padding="same", activation="relu"))
model.add(MaxPooling2D(pool_size=(2,2),strides=(2,2)))

# L11-13
model.add(Conv2D(filters=512, kernel_size=(3,3), padding="same", activation="relu"))
model.add(Conv2D(filters=512, kernel_size=(3,3), padding="same", activation="relu"))
model.add(Conv2D(filters=512, kernel_size=(3,3), padding="same", activation="relu"))
model.add(MaxPooling2D(pool_size=(2,2),strides=(2,2),name='vgg16'))

model.add(Flatten(name='flatten'))
# L14 - Fully nected 1
model.add(Dense(4096, activation='relu', name='fc1'))
# L15 - Fully nected 2
model.add(Dense(4096, activation='relu', name='fc2'))
# L16
model.add(Dense(1000, activation='softmax', name='output'))
model.summary()

Popularity 9/10 Helpfulness 2/10 Language python

Source: Grepper

Tags: architecture python

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Contributed on Nov 20 2023

Pouty Parrot

0 Answers Avg Quality 2/10

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vgg16 application

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tf.keras.applications.VGG16(
    include_top=True,
    weights="imagenet",
    input_tensor=None,
    input_shape=None,
    pooling=None,
    classes=1000,
    classifier_activation="softmax",
)

Popularity 10/10 Helpfulness 1/10 Language whatever

Source: keras.io

Tags: whatever whateve

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Contributed on Jun 01 2021

Powerful Pintail

0 Answers Avg Quality 2/10

vgg16 architecture

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