A comprehensive survey on applications of transformers for deep learning tasks

S Islam, H Elmekki, A Elsebai, J Bentahar… - Expert Systems with …, 2024‏ - Elsevier
Abstract Transformers are Deep Neural Networks (DNN) that utilize a self-attention
mechanism to capture contextual relationships within sequential data. Unlike traditional …

Deep learning in hydrology and water resources disciplines: Concepts, methods, applications, and research directions

KP Tripathy, AK Mishra - Journal of Hydrology, 2024‏ - Elsevier
Over the past few years, Deep Learning (DL) methods have garnered substantial
recognition within the field of hydrology and water resources applications. Beginning with a …

An efficient artificial rabbits optimization based on mutation strategy for skin cancer prediction

M Abd Elaziz, A Dahou, A Mabrouk… - Computers in Biology …, 2023‏ - Elsevier
Accurate skin lesion diagnosis is critical for the early detection of melanoma. However, the
existing approaches are unable to attain substantial levels of accuracy. Recently, pre-trained …

A novel vision transformer model for skin cancer classification

G Yang, S Luo, P Greer - Neural Processing Letters, 2023‏ - Springer
Skin cancer can be fatal if it is found to be malignant. Modern diagnosis of skin cancer
heavily relies on visual inspection through clinical screening, dermoscopy, or …

Boundary guided semantic learning for real-time COVID-19 lung infection segmentation system

R Cong, Y Zhang, N Yang, H Li, X Zhang… - IEEE Transactions …, 2022‏ - ieeexplore.ieee.org
The coronavirus disease 2019 (COVID-19) continues to have a negative impact on
healthcare systems around the world, though the vaccines have been developed and …

Transy-net: Learning fully transformer networks for change detection of remote sensing images

T Yan, Z Wan, P Zhang, G Cheng… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
In the remote sensing field, change detection (CD) aims to identify and localize the changed
regions from dual-phase images over the same places. Recently, it has achieved great …

Classification for thyroid nodule using ViT with contrastive learning in ultrasound images

J Sun, B Wu, T Zhao, L Gao, K **e, T Lin, J Sui… - Computers in biology …, 2023‏ - Elsevier
The lack of representative features between benign nodules, especially level 3 of Thyroid
Imaging Reporting and Data System (TI-RADS), and malignant nodules limits diagnostic …