In 1989, Yann LeCun published the paper "Backpropagation Applied to Handwritten Zip Code Recognition", which introduced the application of convolutional neural network CNN in handwritten character recognition and laid the foundation for CNN. Convolutional neural network is a kind of neural network that can effectively process image data. It uses operations such as convolution and pooling to extract features from input images and use these features for tasks such as classification and recognition. The emergence of convolutional neural network has made neural network widely used in the field of computer vision and has become an indispensable part of deep learning technology.
In general, the early 1980s was a period of resurgence iceland mobile database of artificial intelligence technology, and also the starting stage of neural network and deep learning technology. The introduction of basic algorithms and technologies such as back propagation algorithm and convolutional neural network laid the foundation for the subsequent development of deep learning technology and laid a solid foundation for the application and promotion of neural networks in various industries.
The crisis of deep learning technology
In the 1990s and early 2000s, deep learning technology encountered a period of lows, known as the "deep learning crisis". During this period, the application scope of neural networks and deep learning technology was limited, research enthusiasm and investment decreased, and many people were pessimistic about the prospects of neural networks and deep learning technology. The main reasons include: