A review on the attention mechanism of deep learning

By Zhaoyang Niu, Guoqiang Zhong, Hui Yu. Neurocomputing, 2021

3,043 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/a56bf7ee9a56d8f84079684339a953c2df9ce76b

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. Yichao Liu
2. Iqbal H. Sarker
3. Nico Hoffmann
4. Zongru Shao
5. Mohammad Mustafa Taye

In Computer Vision and Pattern Recognition

1. Yichao Liu
2. Iqbal H. Sarker
3. Nico Hoffmann
4. Zongru Shao

Citations in the corpus

• Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Research Directions (2021, background): “Similarly, domain knowledge in medical image analysis [58], financial sentiment analysis [49], cybersecurity analytics [94, 103] as well as conceptual data model in which semantic information, (i.e., meaningful for a system, rather than merely correlational) [45, 121, 131] is etc [13, 80].”
• Global Attention Mechanism: Retain Information to Enhance Channel-Spatial Interactions (2021, background): “The attention mechanisms have been improving performance in multiple applications and attracted research interests in recent years (Niu et al. [2021]).”