An older article by jjwalkarn about Convolutional Neural Networks. Convolutional Neural Networks (ConvNets or CNNs) are a category of Neural Networks that have proven very effective in areas such as image recognition and classification.
ConvNets have been successful in identifying faces, objects and traffic signs apart from powering vision in robots and self driving cars.
The LeNet Architecture is few decades old. LeNet was one of the very first convolutional neural networks which helped propel the field of Deep Learning. This pioneering work by Yann LeCun was named LeNet5 after many previous successful iterations since the year 1988.
The article then explain in detail main operations in the ConvNet:
- Convolution
- Non Linearity (ReLU)
- Pooling or Sub Sampling
- Classification (Fully Connected Layer)
In the article you get the main concepts behind Convolutional Neural Networks in simple terms. Plus, added is a treasure of links to further reading. Excellent read!
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