A comprehensive survey on applications of transformers for deep learning tasks

Saidul Islam, Hanae Elmekki, Ahmed Elsebai, Jamal Bentahar, Nagat Drawel, Gaith Rjoub, Witold Pedrycz

Abstract: Highlights•The paper presents a comprehensive survey on transformers for deep learning tasks.•The paper conducts a thorough analysis on highly effective models in five domains.•The paper classifies the models based on respective tasks using a proposed taxonomy.•The characteristics of the surveyed models are deeply explored and analyzed.•Future directions and challenges for transformer-based models are deciphered.