Article-Journal

PViTGAtt-IP: Severity Quantification of Lung Infections in Chest X-rays and CT Scans via Parallel and Cross-Attended Encoders
The development of a robust and adaptive deep learning technique for the diagnosis of pneumonia and the assessment of its severity was …
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Label-free metabolic fingerprinting of motile mammalian spermatozoa with subcellular resolution
Background: Sperm metabolic pathways that generate energy for motility are compartmentalized within the flagellum. Dysfunctions in …
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Leveraging Graph Convolutional Networks for Semi-supervised Learning in Multi-view Non-graph Data
Semi-supervised learning with a graph-based approach has gained prominence in machine learning, particularly in scenarios where …
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Semi-supervised learning for multi-view and non-graph data using Graph Convolutional Networks
Semi-supervised learning with a graph-based approach has become increasingly popular in machine learning, particularly when dealing …
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Semi-supervised learning for multi-view and non-graph data using Graph Convolutional Networks
Cosine Additive Angular Margin Loss for Breast Cancer Classification in Histopathological Images with Small AI Systems
Breast cancer claims thousands of lives annually, emphasizing the need for swift and accurate histopathology image classification to …
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Enhancing Generalization and Mitigating Overfitting in Deep Learning for Brain Cancer Diagnosis from MRI
Brain cancer represents a significant global health challenge with increasing incidence and mortality rates. Magnetic Resonance Imaging …
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Unified multi-view data clustering: Simultaneous learning of consensus coefficient matrix and similarity graph
Integrating data from multiple sources or views has become increasingly common in data analysis, particularly in fields like …
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Enhancing MRI brain tumor classification: A comprehensive approach integrating real-life scenario simulation and augmentation techniques
Brain cancer poses a significant global health challenge, with mortality rates showing a concerning surge over recent decades. The …
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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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HSMix: Hard and soft mixing data augmentation for medical image segmentation
Due to the high cost of annotation or the rarity of some diseases, medical image segmentation is often limited by data scarcity and the …
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