深度学习
人工智能
计算机科学
循环神经网络
卷积神经网络
深信不疑网络
强化学习
机器学习
人工神经网络
作者
Rekha Miriyala Kanthi,Lakshmi Gorle Dhana,Suneetha Eluri
出处
期刊:i-manager's journal on pattern recognition
[i-manager Publications]
日期:2022-01-01
卷期号:9 (1): 33-33
标识
DOI:10.26634/jpr.9.1.18858
摘要
In recent years, machine learning and Deep Learning have increased and gathered epic success in traditional application domains and new areas of Artificial Intelligence. The performance using Deep Learning has dominated experimental results compared to conventional machine learning algorithms. This paper presents an overview of the progress that has occurred in Deep Learning (DL) concerning some application domains like Autonomous Driving, Healthcare, Voice Recognition, Image Recognition, Advertising, Predicting Natural Calamities, National Stock Exchange and many more. Additionally, deeper insights into several Deep Learning techniques, their working principles, and experimental results are scrutinized. The survey covers Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), including Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU), Auto-Encoder (AE), Deep Belief Network (DBN), Generative Adversarial Network (GAN), and Deep Reinforcement Learning (DRL).
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