深度学习
人工智能
计算机科学
多样性(控制论)
卷积神经网络
数据科学
生成语法
对抗制
人工神经网络
机器学习
深层神经网络
循环神经网络
作者
B. Yamini,Viktor K. Prasanna,C. Ambhika,M Anuradha,B. Uma Maheswari,Siva Subramanian. R,M. Nalini
出处
期刊:International Journal on Recent and Innovation Trends in Computing and Communication
[Auricle Technologies Pvt., Ltd.]
日期:2023-08-18
卷期号:11 (8s): 445-453
标识
DOI:10.17762/ijritcc.v11i8s.7225
摘要
Artificial intelligence's "deep learning" discipline has taken off, revolutionizing a variety of industries, from computer vision and natural language processing to healthcare and finance. Deep learning has shown extraordinary effectiveness in resolving complicated issues, and it has a wide range of potential applications, from autonomous vehicles to healthcare. The purpose of the survey to study deep learning's present condition, including recent advancements, difficulties, and constraints since the subject is currently fast growing. The basic ideas of deep learning, such as neural networks, activation functions, and optimization algorithms, are first introduced. We next explore numerous topologies, emphasizing their distinct properties and uses, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs). Further concepts, applications, and difficulties of deep learning are all covered in this survey paper's thorough review. This survey aid the academics, professionals, and individuals who want to learn more about deep learning and explore its applications to challenging situations in the real world.
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