Results 31 to 40 of about 25,505 (263)
V-LTCS: Backbone exploration for Multimodal Misogynous Meme detection
Memes have become a fundamental part of online communication and humour, reflecting and shaping the culture of today’s digital age. The amplified Meme culture is inadvertently endorsing and propagating casual Misogyny. This study proposes V-LTCS (Vision-
Sneha Chinivar +3 more
doaj +1 more source
Improving diagnosis and prognosis of lung cancer using vision transformers: a scoping review
Background Vision transformer-based methods are advancing the field of medical artificial intelligence and cancer imaging, including lung cancer applications.
Hazrat Ali, Farida Mohsen, Zubair Shah
doaj +1 more source
Semi-supervised Vision Transformers
We study the training of Vision Transformers for semi-supervised image classification. Transformers have recently demonstrated impressive performance on a multitude of supervised learning tasks. Surprisingly, we show Vision Transformers perform significantly worse than Convolutional Neural Networks when only a small set of labeled data is available ...
Zejia Weng +4 more
openaire +3 more sources
GaitTriViT and GaitVViT: Transformer-based methods emphasizing spatial or temporal aspects in gait recognition [PDF]
In image recognition tasks, subjects with long distances and low resolution remain a challenge, whereas gait recognition, identifying subjects by walking patterns, is considered one of the most promising biometric technologies due to its stability and ...
Hongyun Sheng
doaj +2 more sources
RT-ViT: Real-Time Monocular Depth Estimation Using Lightweight Vision Transformers
The latest research in computer vision highlighted the effectiveness of the vision transformers (ViT) in performing several computer vision tasks; they can efficiently understand and process the image globally unlike the convolution which processes the ...
Hatem Ibrahem +2 more
doaj +1 more source
Transforming glaucoma diagnosis: transformers at the forefront
Although the Vision Transformer architecture has become widely accepted as the standard for image classification tasks, using it for object detection in computer vision poses significant challenges.
Farheen Chincholi, Harald Koestler
doaj +1 more source
Vision Transformers (ViTs) have recently become the state-of-the-art across many computer vision tasks. In contrast to convolutional networks (CNNs), ViTs enable global information sharing even within shallow layers of a network, i.e., among high-resolution features. However, this perk was later overlooked with the success of pyramid architectures such
Jongwoo Park 0003 +5 more
openaire +2 more sources
MOGAD Is the Most Common Cause of Isolated Optic Neuritis in Children
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
Leveraging Transfer Learning for Accurate CRP Level Prediction in Diabetic Patients
This study addresses the challenge of predicting C-reactive protein (CRP) levels in patients with type 2 diabetes mellitus by integrating tabular-to-image transformation techniques with transfer learning architectures.
Alaa J. Albaqal, Mardin A. Anwar
doaj +1 more source
ABSTRACT Objective Building on our prior Behavioral Risk Factor Surveillance System analysis identifying adults aged 18–39 as the primary driver of the national increase in self‐reported cognitive disability, we examined factors associated with this rise using 2013–2024 U.S. BRFSS data. Methods We analyzed U.S.
Adam de Havenon +9 more
wiley +1 more source

