Results 61 to 70 of about 1,457,631 (249)

Natural Frequencies of Levodopa‐Induced Dyskinesia in Parkinson's Disease

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Abnormal involuntary movements, known as dyskinesias, are common complications of levodopa treatment in patients with Parkinson's disease and can significantly impair quality of life. The underlying pathophysiology remains unclear, and current therapeutic options are limited.
Ioannis U. Isaias   +3 more
wiley   +1 more source

Vision Transformers in medical computer vision—A contemplative retrospection

open access: yesEngineering Applications of Artificial Intelligence, 2023
Recent escalation in the field of computer vision underpins a huddle of algorithms with the magnificent potential to unravel the information contained within images. These computer vision algorithms are being practised in medical image analysis and are transfiguring the perception and interpretation of Imaging data.
Arshi Parvaiz   +5 more
openaire   +3 more sources

Gravity‐Dependent Modulation of Downbeat Nystagmus: Insights From Velocity‐Storage Dysfunction

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Downbeat nystagmus varies with head position, a phenomenon termed gravity‐dependent modulation. We aimed to clarify its mechanism using a velocity‐storage model. Methods In 10 patients with downbeat nystagmus due to cerebellar disorders, we recorded eye movements at different pitch‐ and roll‐axis head positions.
Ji‐Hyung Park   +5 more
wiley   +1 more source

Towards Robust Vision Transformer [PDF]

open access: yes, 2022
Recent advances on Vision Transformer (ViT) and its improved variants have shown that self-attention-based networks surpass traditional Convolutional Neural Networks (CNNs) in most vision tasks.
Mao, Xiaofeng   +7 more
core   +1 more source

Evaluation of vision transformers for the detection of fullness of garbage bins for efficient waste management

open access: yesFrontiers in Artificial Intelligence
Efficient waste management is crucial for urban environments to maintain cleanliness, reduce environmental impact, and optimize resource allocation. Traditional waste collection systems often rely on scheduled pickups or manual inspections, leading to ...
Parakram Singh Tanwer   +4 more
doaj   +1 more source

Denoising Vision Transformers

open access: yes
Accepted to ECCV2024. Project website: https://jiawei-yang.github.io/DenoisingViT/
Jiawei Yang 0002   +8 more
openaire   +3 more sources

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

open access: yesArthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos   +2 more
wiley   +1 more source

Partial Discharge Location within a Transformer Winding using Principal Component Analysis

open access: yes, 2011
Partial discharge (PD) may occur in a transformer winding due to ageing processes, operational over stressing or defects introduced during manufacture. The presence of PD does not necessarily indicate imminent failure of the transformer but it will lead ...
Abd Rahman, M S, Hao, L, Lewin, P L
core   +1 more source

Transformer With Linear-Window Attention for Feature Matching

open access: yesIEEE Access, 2023
A transformer can capture long-term dependencies through an attention mechanism, and hence, can be applied to various vision tasks. However, its secondary computational complexity is a major obstacle in vision tasks that require accurate predictions.
Zhiwei Shen, Bin Kong, Xiaoyu Dong
doaj   +1 more source

Quantum Vision Transformers

open access: yesQuantum
In this work, quantum transformers are designed and analysed in detail by extending the state-of-the-art classical transformer neural network architectures known to be very performant in natural language processing and image analysis. Building upon the previous work, which uses parametrised quantum circuits for data loading and orthogonal neural layers,
El Amine Cherrat   +5 more
openaire   +4 more sources

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