A Survey of Deep Learning and Its Applications: A New Paradigm to Machine Learning

By Shaveta Dargan, Munish Kumar, Maruthi Rohit Ayyagari, G. Kumar. Archives of Computational Methods in Engineering, 2019

1,035 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/e67121cd31e95fba6c892724e619323ad7564b03

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. Gianluigi Rozza
2. Francesco Piccialli
3. Fabio Giampaolo
4. Salvatore Cuomo
5. Vincenzo Schiano Di Cola
6. Maizar Raissi
7. G. Em Karniadakis
8. Paris Perdikaris

In Computer Vision and Pattern Recognition

1. Fabio Giampaolo
2. Salvatore Cuomo
3. Francesco Piccialli
4. Gianluigi Rozza
5. Vincenzo Schiano Di Cola
6. Maizar Raissi
7. Paris Perdikaris
8. G. Em Karniadakis

In Radiology, Nuclear Medicine and Imaging

1. Maizar Raissi

Citations in the corpus

• Scientific Machine Learning Through Physics–Informed Neural Networks: Where we are and What’s Next (2022, background): “Many alternative architectures are proposed in the DL literature [35], and PINN development can benefit from thiswide range of combinations in such researchfields.”