The LeNet-5 convolutional neural network

LeNet-5 is a seven-level convolutional neural network, published by the team comprising of Yann LeCunn, Yoshua Bengio, Leon Bottou and Patrick Haffner in 1998 to classify digits, which was used by banks to recognize handwritten numbers on checks. The layers are ordered as:

• Input image | Convolutional Layer 1(ReLU) | Pooling 1 |Convolutional Layer 2(ReLU) |Pooling 2 |Fully Connected (ReLU) 1 | Fully Connected 2 | Output
• LeNet-5 had remarkable results, but the ability to process higher-resolution images required more convolutional layers, such as in AlexNet, VGG-Net, and Inception models.