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DL4MicEverywhere: deep learning for microscopy made flexible, shareable and reproducible
DL4MicEverywhere is a platform that lets users train and implement their models in different computational environments. These …
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DL4MicEverywhere: deep learning for microscopy made flexible, shareable and reproducible
Emb-trattunet: a novel edge loss function and transformer-CNN architecture for multi-classes pneumonia infection segmentation in low annotation regimes
One of the primary challenges in applying deep learning approaches to medical imaging is the limited availability of data due to …
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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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Facial Age Estimation Using Multi-Stage Deep Neural Networks
Over the last decade, the world has witnessed many breakthroughs in artificial intelligence, largely due to advances in deep learning …
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LCAMix: Local-and-contour aware grid mixing based data augmentation for medical image segmentation
Medical image segmentation often faces challenges related to overfitting, primarily due to the limited and complex training samples. …
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LCAMix: Local-and-contour aware grid mixing based data augmentation for medical image segmentation
LGCOAMix: Local and Global Context-and-Object-Part-Aware Superpixel-Based Data Augmentation for Deep Visual Recognition
Cutmix-based data augmentation, which uses a cut-and-paste strategy, has shown remarkable generalization capabilities in deep learning. …
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LGCOAMix: Local and Global Context-and-Object-Part-Aware Superpixel-Based Data Augmentation for Deep Visual Recognition
Lung pneumonia severity scoring in chest X-ray images using transformers
To create robust and adaptable methods for lung pneumonia diagnosis and the assessment of its severity using chest X-rays (CXR), access …
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Mises-Fisher similarity-based boosted additive angular margin loss for breast cancer classification
To enhance the accuracy of breast cancer diagnosis, current practices rely on biopsies and microscopic examinations. However, this …
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Naturalize revolution: unprecedented ai-driven precision in skin cancer classification using deep learning
Background: In response to the escalating global concerns surrounding skin cancer, this study aims to address the imperative for …
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Overcoming graph topology imbalance for inductive and scalable semi-supervised learning
Graph-based semi-supervised learning (GSSL) has received much attention recently. Despite some progress made in this area by some …
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