A Review of Machine Learning and Deep Learning Applications

By Pramila P. Shinde, Seema Shah. International Conference on Computing Communication Control and automation, 2018

575 citations recorded by the source corpus.

Machine learning is one of the fields in the modern computing world. A plenty of research has been undertaken to make machines intelligent. Learning is a natural human behavior which has been made an essential aspect of the machines as well. There are various techniques devised for the same. Traditional machine learning algorithms have been applied in many application areas. Researchers have put many efforts to improve the accuracy of that machinelearning algorithms. Another dimension was given thought which leads to deep learning concept. Deep learning is a subset of machine learning. So far few applications of deep learning have been explored. This is definitely going to cater to solving issues in several new application domains, sub-domains using deep learning. A review of these past and future application domains, sub-domains, and applications of machine learning and deep learning are illustrated in this paper.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/4135da4cc0ef70917e45ae4436e7a6411077325c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Zhong Fan
2. Aidan Fuller
3. Thinagaran Perumal
4. Norwati Mustapha
5. Charles Day
6. Raihani Mohamed
7. Farhad Shiri

In Computer Vision and Pattern Recognition

1. Zhong Fan
2. Aidan Fuller
3. Thinagaran Perumal
4. Norwati Mustapha
5. Charles Day
6. Raihani Mohamed
7. Farhad Shiri

In Radiology, Nuclear Medicine and Imaging

1. Zhong Fan
2. Aidan Fuller
3. Charles Day

Citations in the corpus

• A Comprehensive Overview and Comparative Analysis on Deep Learning Models: CNN, RNN, LSTM, GRU (2023, background): “In computer science, AI refers to the study of "intelligent agents," which are objects capable of perceiving their environment and taking actions to maximize their chances of achieving specific goals [1].”
• Digital Twin: Enabling Technologies, Challenges and Open Research (2020, methodology): “The user then analyses these answers and any errors are corrected and re-learned, helping train the model and increasing the accuracy of a given algorithm [70].”