Source-linked AI summary
Review of Deep Learning
Rong Zhang, Weiping Li, Tong Mo
TL;DR
Deep learning is a key area of artificial-intelligence research amid increasing investment. This paper reviews its basic and emerging models, applications, research progress, future directions, and existing problems.
Problem
Deep learning has become a key area of artificial-intelligence research as countries and high-tech companies increase investment in artificial intelligence.
Method
The paper outlines multilayer perceptrons, convolutional neural networks, and recurrent neural networks, then examines convolutional and recurrent-network variants.
Results
The paper summarizes recent deep-learning progress, future research directions, and applications across artificial-intelligence areas.
Takeaways & Limitations
The review organizes deep learning around foundational models, emerging model developments, applications, and possible solutions to existing problems.
Takeaways & Limitations
Recurrent neural networks have gradient vanishing or gradient explosion problems, while deep learning is also vulnerable to adversarial-sample attacks.
Abstract
from arXiv · showhide
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 research's 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 learning's applications in many areas of artificial intelligence, including speech processing, computer vision, natural language processing and so on. Finally, this paper discusses the existing problems of deep learning and gives the corresponding possible solutions.