3D-Vision-Transformer Stacking Ensemble for Assessing Prostate Cancer Aggressiveness from T2w Images
Bioengineering, 2023 Vision transformers represent the cutting-edge topic in computer vision and are usually employed on two-dimensional data following a transfer learning approach.
Eva Pachetti, Sara Colantonio
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Measurements With A Quantum Vision Transformer: A Naive Approach [PDF]
EPJ Web of ConferencesIn mainstream machine learning, transformers are gaining widespread usage. As Vision Transformers rise in popularity in computer vision, they now aim to tackle a wide variety of machine learning applications.
Pasquali Dominic +2 more
doaj +1 more source
Vision Transformers in Image Restoration: A Survey
Sensors, 2023 The Vision Transformer (ViT) architecture has been remarkably successful in image restoration. For a while, Convolutional Neural Networks (CNN) predominated in most computer vision tasks.
Anas M. Ali +5 more
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Variable-Rate Deep Image Compression With Vision Transformers
IEEE Access, 2022 Recently, vision transformers have been applied in many computer vision problems due to its long-range learning ability. However, it has not been throughly explored in image compression.
Binglin Li, Jie Liang, Jingning Han
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EnViTSA: Ensemble of Vision Transformer with SpecAugment for Acoustic Event Classification
Sensors, 2023 Recent successes in deep learning have inspired researchers to apply deep neural networks to Acoustic Event Classification (AEC). While deep learning methods can train effective AEC models, they are susceptible to overfitting due to the models’ high ...
Kian Ming Lim +3 more
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Comparative Effectiveness and Safety of Inebilizumab Versus Rituximab in AQP4‐IgG‐Positive NMOSD
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Rituximab (anti‐CD20, RTX) and inebilizumab (anti‐CD19, INE) represent B‐cell‐depleting therapies used for aquaporin‐4 antibody‐positive (AQP4‐IgG+) neuromyelitis optica spectrum disorder (NMOSD); however, direct comparative evidence remains limited.
Jie Lin +11 more
wiley +1 more source
Permeability Prediction Using Vision Transformers
Mathematical and Computational ApplicationsAccurate permeability predictions remain pivotal for understanding fluid flow in porous media, influencing crucial operations across petroleum engineering, hydrogeology, and related fields.
Cenk Temizel +5 more
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Through-Ice Acoustic Source Tracking Using Vision Transformers with Ordinal Classification
Sensors, 2022 Ice environments pose challenges for conventional underwater acoustic localization techniques due to their multipath and non-linear nature. In this paper, we compare different deep learning networks, such as Transformers, Convolutional Neural Networks ...
Steven Whitaker +3 more
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MOGAD Is the Most Common Cause of Isolated Optic Neuritis in Children
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objectives The study aimed to characterize the clinical features, etiologies, and outcomes of isolated, first‐time pediatric ON in the post‐MOG‐IgG era. Methods This was a single‐center retrospective cohort study at Texas Children's Hospital of patients diagnosed with first‐time ON between 2018–2024, with follow‐up data collected through 2025.
Chaitanya Aduru +13 more
wiley +1 more source
A vision transformer machine learning model for COVID-19 diagnosis using chest X-ray images
Healthcare AnalyticsThis study leverages machine learning to enhance the diagnostic accuracy of COVID-19 using chest X-rays. The study evaluates various architectures, including efficient neural networks (EfficientNet), multiscale vision transformers (MViT), efficient ...
Tianyi Chen +6 more
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