# Computer Vision CNN Architectures

Source: [https://docs.qualcomm.com/doc/80-63442-4/topic/computer-vision-cnn-architectures.html](https://docs.qualcomm.com/doc/80-63442-4/topic/computer-vision-cnn-architectures.html)

Three classic network architectures for combining layers to increase
        accuracy

In essence, the neural network replicates the same process that humans undergo in
            learning from their mistakes. In addition to that neural process, convolution in CNN
            performs the process of feature extraction.

Here are three classic networks and the architecture that underlies each one.

## LeNet-5

LeNet is the first CNN architecture and an example of a gradient-based learning.

LeNet was trained on the Modified NIST or MNIST data set and designed to identify
                handwritten numbers on checks. The weights and hyperparameters are varied so that
                the gradient divergence on the loss function reaches a minimum. But as used in
                computer vision, the weights and hyperparameters in LeNet were engineered manually.
                The input for LeNet is 32×32, which is visible without magnification and far larger
                than the size of the characters as originally written. The large input allows for
                minute features from the image to be captured.

LeNet consists of convolution layers, subsampling layers and fully connected layers.
                (For a diagram of the architecture of LeNet-5, see [http://yann.lecun.com/exdb/publis/pdf/lecun-01a.pdf](http://yann.lecun.com/exdb/publis/pdf/lecun-01a.pdf),
                page 7).

- The convolution layers extract the features from the images.
- The subsampling layer consists of applying the activation function to the input
                    from convolution layers and performing the pooling process on the output
                    obtained from applying activation function.
- A fully connected layer connects each neuron of one layer to every neuron of
                    another layer. The last layer of the fully connected layer is reserved for an
                    activation function to assist in classification.

## AlexNet

The LeNet architecture shows that increasing the depth of the network increases
                accuracy. The AlexNet architecture incorporates that lesson. AlexNet consists of
                five Convolution layers and three fully connected layers.

AlexNet uses ReLu (Rectified Linear Unit) as its activation function. ReLu is used
                instead of traditional sigmoid or tanh functions for introducing non-linearity into
                the network. Compared to traditional activation functions, ReLu is more responsive
                to positive values and zero-responsive to negative values, ensuring that not all the
                neurons are active at any given time. The computation time required for ReLu is also
                lower than that for sigmoid and tanh.

The other advantage of ReLu is that it allows for removing (dropping) dead neurons,
                as shown below.
Figure : Dropout in AlexNet

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)

The developer can set the ratio for dropping inactive neurons. Dropout helps avoid
                overfitting in AlexNet.

When trained on the ImageNet LSVRC-2012 data set, AlexNet achieved a relatively low
                error rate of 15.3% compared to the error rate of 26.2% for a non-CNN. (For a
                diagram of the architecture of AlexNet, see [https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf](https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf),
                page 5.

## VGG-Net (Visual Geometry Group)

AlexNet demonstrates the value of using larger filters. To attain the state of the
                art, VGG-Net uses 3×3 filters in a series. That increases the depth of the network,
                which is effective in detecting the features in an image. (For a diagram of the
                architecture of VGG-Net, trained and tested on a data set containing 1000 classes,
                with 1000 images in each class, see [https://www.researchgate.net/profile/Clifford_Yang/publication/325137356/figure/fig2/AS:670371271413777@1536840374533/llustration-of-the-network-architecture-of-VGG-19-model-conv-means-convolution-FC-means.jpg](https://www.researchgate.net/profile/Clifford_Yang/publication/325137356/figure/fig2/AS:670371271413777@1536840374533/llustration-of-the-network-architecture-of-VGG-19-model-conv-means-convolution-FC-means.jpg)

**Parent Topic:** [CNN Architectures](https://docs.qualcomm.com/doc/80-63442-4/topic/cnn-architectures.html)

Last Published: Jun 24, 2024

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