Deep learning has become the most widely used approach for cardiac image segmentation
in recent years. In this paper, we provide a review of over 100 cardiac image segmentation …

Over the past few decades, interest in theories and algorithms for face recognition has been
growing rapidly. Video surveillance, criminal identification, building access control, and …

Learning with few labeled data has been a longstanding problem in the computer vision and
machine learning research community. In this paper, we introduced a new semi-supervised …

Recent advances in machine learning have led to increased interest in solving visual
computing problems using methods that employ coordinate‐based neural networks. These …

Starting around 6 to 9 months of age, children begin acquiring their first words, linking
spoken words to their visual counterparts. How much of this knowledge is learnable from …

Detecting COVID-19 early may help in devising an appropriate treatment plan and disease
containment decisions. In this study, we demonstrate how transfer learning from deep …

The COVID-19 pandemic is causing a major outbreak in more than 150 countries around the
world, having a severe impact on the health and life of many people globally. One of the …

Deep neural networks excel at finding hierarchical representations that solve complex tasks
over large datasets. How can we humans understand these learned representations? In this …

Lymph node metastasis in breast cancer may be accurately predicted using a DenseNet-
169 model. However, the current system for identifying metastases in a lymph node is …

Monkeypox has become a significant global challenge as the number of cases increases
daily. Those infected with the disease often display various skin symptoms and can spread …