Cifar-10 Classifier Using CNN

Access and run the notebook on kaggle

Dataset

Dataset Link: https://www.cs.toronto.edu/~kriz/cifar.html

Accuracy acheived after training

For 120 Epochs

• Training Acc: 93.43%
• Validation Acc: 90.01%
• Test Acc: 89.39%

Model Architecture

def get_cnn_model(activation = "relu"):
    model = Sequential()
    model.add(Conv2D(96, (3, 3), activation=activation, kernel_initializer='he_uniform', padding='same', input_shape=(32, 32, 3)))
    model.add(BatchNormalization())

    model.add(Conv2D(96, (3, 3), activation=activation, kernel_initializer='he_uniform', padding='same'))
    model.add(BatchNormalization())
    model.add(MaxPooling2D((2, 2)))
    model.add(Dropout(0.2))

    model.add(Conv2D(96, (3, 3), activation=activation, kernel_initializer='he_uniform', padding='same'))
    model.add(BatchNormalization())

    model.add(Conv2D(192, (3, 3), activation=activation, kernel_initializer='he_uniform', padding='same'))
    model.add(BatchNormalization())
    model.add(MaxPooling2D((2, 2)))
    model.add(Dropout(0.3))

    model.add(Conv2D(192, (3, 3), activation=activation, kernel_initializer='he_uniform', padding='same'))
    model.add(BatchNormalization())

    model.add(Conv2D(192, (3, 3), activation=activation, kernel_initializer='he_uniform', padding='same'))
    model.add(BatchNormalization())
    model.add(MaxPooling2D((2, 2)))
    model.add(Dropout(0.4))

    model.add(Conv2D(256, (3, 3), activation=activation, kernel_initializer='he_uniform', padding='same'))
    model.add(BatchNormalization())

    model.add(Conv2D(256, (3, 3), activation=activation, kernel_initializer='he_uniform', padding='same'))
    model.add(BatchNormalization())
    model.add(MaxPooling2D((2, 2)))
    model.add(Dropout(0.4))

    model.add(Flatten())

    model.add(Dense(128, activation=activation, kernel_initializer='he_uniform'))
    model.add(BatchNormalization())
    model.add(Dropout(0.5))

    model.add(Dense(10, activation='softmax'))

    return model

Accuracy, Loss and Precision

Model Prediciton