A General Survey on Attention Mechanisms in Deep Learning

03/27/2022
by   Gianni Brauwers, et al.
0

Attention is an important mechanism that can be employed for a variety of deep learning models across many different domains and tasks. This survey provides an overview of the most important attention mechanisms proposed in the literature. The various attention mechanisms are explained by means of a framework consisting of a general attention model, uniform notation, and a comprehensive taxonomy of attention mechanisms. Furthermore, the various measures for evaluating attention models are reviewed, and methods to characterize the structure of attention models based on the proposed framework are discussed. Last, future work in the field of attention models is considered.

READ FULL TEXT
research
04/05/2019

An Attentive Survey of Attention Models

Attention Model has now become an important concept in neural networks t...
research
04/16/2022

Visual Attention Methods in Deep Learning: An In-Depth Survey

Inspired by the human cognitive system, attention is a mechanism that im...
research
12/11/2021

Neural Attention Models in Deep Learning: Survey and Taxonomy

Attention is a state of arousal capable of dealing with limited processi...
research
09/05/2023

Enhancing Deep Learning Models through Tensorization: A Comprehensive Survey and Framework

The burgeoning growth of public domain data and the increasing complexit...
research
04/26/2022

A survey on attention mechanisms for medical applications: are we moving towards better algorithms?

The increasing popularity of attention mechanisms in deep learning algor...
research
11/28/2017

Intelligent Notification Systems: A Survey of the State of the Art and Research Challenges

Notifications provide a unique mechanism for increasing the effectivenes...
research
06/05/2023

Infusing Lattice Symmetry Priors in Attention Mechanisms for Sample-Efficient Abstract Geometric Reasoning

The Abstraction and Reasoning Corpus (ARC) (Chollet, 2019) and its most ...

Please sign up or login with your details

Forgot password? Click here to reset