Capsule Networks:

• CapsNet: Capsule Networks are an advanced neural network architecture that can represent spatial relationships between objects in an image better than CNNs.

pythonCopy codefrom tensorflow.keras import layers, models

# Define capsule layer
def capsule_layer(inputs, num_capsules, dim_capsules):
    u_hat = layers.Conv2D(num_capsules * dim_capsules, kernel_size=9, strides=1, padding='valid')(inputs)
    u_hat_reshaped = layers.Reshape((num_capsules, dim_capsules))(u_hat)
    return layers.Lambda(squash)(u_hat_reshaped)

# Squash function
def squash(x):
    s_squared_norm = K.sum(K.square(x), axis=-1, keepdims=True)
    scale = s_squared_norm / (1 + s_squared_norm) / K.sqrt(s_squared_norm + K.epsilon())
    return scale * x

inputs = layers.Input(shape=(28, 28, 1))
caps_output = capsule_layer(inputs, num_capsules=10, dim_capsules=16)

model = models.Model(inputs, caps_output)