Computer vision and convolutional neural networks

Computer vision is a key aspect of artificial intelligence that is critical to many applications, from robots movements to self-driving cars and from medical imaging to products recognition in manufacturing plants. This MIT course presents the issues of computer vision and how they are handled with Convolutional Neural Networks together with the latest domains of research and state-of-the-art algorithms architectures.

image classification by a computer

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Catalogue of neural networks architectures

Neural networks come in a wide range of shapes and functions, with diverse architectures and parameters for input, hidden and output nodes as well as convolutive or recurrent nodes.

Overview of the most popular neural networks
Overview of the most popular neural networks

Regrouped in a convenient summary by Fjodor Van Veen, the most popular architectures for neural networks have been cataloged with detailed descriptions for each type of neural network. The complete post with explanations on the use and goals of each network can be be found on the Asimov Institute “the neural network zoo“.