Conference Details

Abstract :

Recently attention model is a crucial technique used in many research domains. It is a fundamental component of all perceptual and cognitive processes. This mechanism select, modify, and concentrate on the information which is most important to behaviour because of our limited capacity to interpret competing sources. For many years, researchers in the fields of philosophy, psychology, neuroscience, and computing have examined the notions and functions of attention. This characteristic has also been thoroughly investigated in deep neural networks over the past six years. In many application domains, neural attention models currently represent the cutting edge of deep learning. In this survey authors analyse the recent advancements in neural attention models. In order to identify and examine the architectures where attention has a notable impact, we thoroughly reviewed. Additionally, we created and made available an automated approach to aid in the growth of reviews in the field. The use of attention model in CNN, RNN and Generative model respectively are cited in this paper. Additionally, it also explores the effects of attention across various application areas.