Name
Abstract | ||
|---|---|---|
In recent years, China, the United States and other countries, Google and other high-tech companies have increased investment in artificial intelligence. Deep learning is one of the current artificial intelligence researchu0027s key areas. This paper analyzes and summarizes the latest progress and future research directions of deep learning. Firstly, three basic models of deep learning are outlined, including multilayer perceptrons, convolutional neural networks, and recurrent neural networks. On this basis, we further analyze the emerging new models of convolution neural networks and recurrent neural networks. This paper then summarizes deep learningu0027s applications in many areas of artificial intelligence, including voice, computer vision, natural language processing and so on. Finally, this paper discusses the existing problems of deep learning and gives the corresponding possible solutions. |
Year | Venue | Field |
|---|---|---|
2018 | arXiv: Learning | Convolution,Convolutional neural network,Recurrent neural network,Artificial intelligence,Deep learning,Artificial neural network,Perceptron,Mathematics,Machine learning |
DocType | Volume | Citations |
Journal | abs/1804.01653 | 8 |
PageRank | References | Authors |
0.90 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rong Zhang | 1 | 704 | 54.69 |
| Weiping Li | 2 | 8 | 1.24 |
| Tong Mo | 3 | 13 | 3.68 |