The semantic image segmentation task consists of classifying each pixel of an image into an
instance, where each instance corresponds to a class. This task is a part of the concept of …

Deep learning (DL) has become widely used for medical image segmentation in recent
years. However, despite these advances, there are still problems for which DL-based …

Smart manufacturing arises the growing demand for predictive analytics to forecast the
deterioration and reliability of equipment. Many machine learning algorithms, especially …

Computer-aided medical image analysis plays a significant role in assisting medical
practitioners for expert clinical diagnosis and deciding the optimal treatment plan. At present …

Background Electrocardiogram (ECG) is one of the most common noninvasive diagnostic
tools that can provide useful information regarding a patient's health status. Deep learning …

Scanning Electron Microscopy (SEM) images provide a variety of structural and
morphological information of nanomaterials. In the material informatics domain, automatic …

Over the past few years, a tremendous change has occurred in computer‐aided diagnosis
(CAD) technology. The evolution of numerous medical imaging techniques has enhanced …

Glaucoma is an eye disease that can cause loss of vision by damaging the optic nerve. It is
the world's second leading cause of blindness after cataracts. Early diagnosis of glaucoma …

Rapid advances in biological research over recent years have significantly enriched
biological and medical data resources. Deep learning-based techniques have been …

Neuroimaging data driven machine learning based predictive modeling and pattern
recognition has been attracted strongly attention in biomedical sciences. Machine learning …