Denoising diffusion models, a class of generative models, have garnered immense interest
lately in various deep-learning problems. A diffusion probabilistic model defines a forward …

Denoising diffusion models, a class of generative models, have garnered immense interest
lately in various deep-learning problems. A diffusion probabilistic model defines a forward …

The Segment Anything Model (SAM) has recently gained popularity in the field of image
segmentation due to its impressive capabilities in various segmentation tasks and its prompt …

Publicly available skin image datasets are increasingly used to develop machine learning
algorithms for skin cancer diagnosis. However, the total number of datasets and their …

Federated Learning (FL) is a novel approach enabling several clients holding sensitive data
to collaboratively train machine learning models, without centralizing data. The cross-silo FL …

Computer-aided systems for skin lesion diagnosis is a growing area of research. Recently,
researchers have shown an increasing interest in developing computer-aided diagnosis …

Supervised learning aims to build a function or model that seeks as many mappings as
possible between the training data and outputs, where each training data will predict as a …

The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …

Convolutional Neural Networks (CNNs) have reigned for a decade as the de facto approach
to automated medical image diagnosis. Recently, vision transformers (ViTs) have appeared …

Artificial intelligence (AI) has wide applications in healthcare, including dermatology.
Machine learning (ML) is a subfield of AI involving statistical models and algorithms that can …