Deep Learning Techniques: An Overview

By Amitha Mathew, P. Amudha, S. Sivakumari. Advances in Intelligent Systems and Computing, 2020

318 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/224c62b9e6ea7d8fb821ec808d26a5875cd555e0

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. Thinagaran Perumal
2. Norwati Mustapha
3. Mohammad Mustafa Taye
4. Raihani Mohamed
5. Farhad Shiri

In Radiology, Nuclear Medicine and Imaging

1. Mohammad Mustafa Taye

Citations in the corpus

• Understanding of Machine Learning with Deep Learning: Architectures, Workflow, Applications and Future Directions (2023, background): “The potential to generate novel features from the limited existing training data. reinforcement learning [28,29].”
• A Comprehensive Overview and Comparative Analysis on Deep Learning Models: CNN, RNN, LSTM, GRU (2023, methodology): “Currently, deep learning methods outperform traditional machine learning approaches [3].”