Article-Journal

Recognizing and detecting COVID-19 in chest X-ray images using constrained multi-view spectral clustering
Machine learning, particularly classification algorithms, has been widely employed for diagnosing COVID-19 cases. However, these …
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Sample-weighted fused graph-based semi-supervised learning on multi-view data
Research in semi-supervised learning on graphs has attracted more and more attention in recent years, as learning on graphs is applied …
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Towards a unified framework for graph-based multi-view clustering
Recently, clustering data collected from various sources has become a hot topic in real-world applications. The most common methods for …
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Towards a unified framework for graph-based multi-view clustering
Towards Self-Conscious AI Using Deep ImageNet Models: Application for Blood Cell Classification
The exceptional performance of ImageNet competition winners in image classification has led AI researchers to repurpose these models …
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Towards unsupervised radiograph clustering for COVID-19: The use of graph-based multi-view clustering
Automatic classification methods widely used for diagnosing and analyzing COVID-19 cases. These methods assume known labels and rely on …
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Transformer-based fall detection in videos
Falls pose a major threat for the elderly as they result in severe consequences for their physical and mental health or even death in …
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3D Domain Adaptive Instance Segmentation Via Cyclic Segmentation GANs
3D instance segmentation for unlabeled imaging modalities is a challenging but essential task as collecting expert annotation can be …
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3D Domain Adaptive Instance Segmentation Via Cyclic Segmentation GANs
A unified deep semi-supervised graph learning scheme based on nodes re-weighting and manifold regularization
In recent years, semi-supervised learning on graphs has gained importance in many fields and applications. The goal is to use both …
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Blood cell revolution: Unveiling 11 distinct types with ‘Naturalize’ augmentation
Artificial intelligence (AI) has emerged as a cutting-edge tool, simultaneously accelerating, securing, and enhancing the diagnosis and …
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Boosted Additive Angular Margin Loss for breast cancer diagnosis from histopathological images
Pathologists use biopsies and microscopic examination to accurately diagnose breast cancer. This process is time-consuming, …
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