Results 41 to 50 of about 1,512,599 (152)
Vision Transformer Adapters for Generalizable Multitask Learning [PDF]
We introduce the first multitasking vision transformer adapters that learn generalizable task affinities which can be applied to novel tasks and domains.
Bhattacharjee, Deblina +2 more
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Semi-supervised Vision Transformers
, 2022 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
Transforming glaucoma diagnosis: transformers at the forefront
Frontiers in Artificial IntelligenceAlthough 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
GaitTriViT and GaitVViT: Transformer-based methods emphasizing spatial or temporal aspects in gait recognition [PDF]
PeerJ Computer ScienceIn 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
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Leveraging Transfer Learning for Accurate CRP Level Prediction in Diabetic Patients
Zanco Journal of Pure and Applied SciencesThis 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
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MoCoViT: Mobile Convolutional Vision Transformer
, 2022 Recently, Transformer networks have achieved impressive results on a variety of vision tasks. However, most of them are computationally expensive and not suitable for real-world mobile applications.
Ma, Hailong +5 more
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2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)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
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Improving diagnosis and prognosis of lung cancer using vision transformers: a scoping review
BMC Medical Imaging, 2023 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
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Gait-ViT: Gait Recognition with Vision Transformer
Sensors, 2022 Identifying an individual based on their physical/behavioral characteristics is known as biometric recognition. Gait is one of the most reliable biometrics due to its advantages, such as being perceivable at a long distance and difficult to replicate ...
Jashila Nair Mogan +3 more
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GGViT:Multistream Vision Transformer Network in Face2Face Facial Reenactment Detection
, 2022 GGViT:Multistream Vision Transformer Network in Face2Face Facial Reenactment ...
Peipei Wang (13088943) +4 more
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