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A comprehensive survey on applications of transformers for deep learning tasks
Abstract Transformers are Deep Neural Networks (DNN) that utilize a self-attention
mechanism to capture contextual relationships within sequential data. Unlike traditional …
mechanism to capture contextual relationships within sequential data. Unlike traditional …
Deep learning in hydrology and water resources disciplines: Concepts, methods, applications, and research directions
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 …
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
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 …
existing approaches are unable to attain substantial levels of accuracy. Recently, pre-trained …
A novel vision transformer model for skin cancer classification
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 …
heavily relies on visual inspection through clinical screening, dermoscopy, or …
Boundary guided semantic learning for real-time COVID-19 lung infection segmentation system
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 …
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
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 …
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 …
Imaging Reporting and Data System (TI-RADS), and malignant nodules limits diagnostic …