Recent advances in deep learning have shown excellent performance in various scene
understanding tasks. However, in some complex environments or under challenging …

Even if measuring the outcome of binary classifications is a pivotal task in machine learning
and statistics, no consensus has been reached yet about which statistical rate to employ to …

Global terrorist threats and illegal migration have intensified concerns for the security of
citizens, and every effort is made to exploit all available technological advances to prevent …

History shows that the infectious disease (COVID-19) can stun the world quickly, causing
massive losses to health, resulting in a profound impact on the lives of billions of people …

When it comes to medical image segmentation on brain MR images, using deep learning
techniques has a significant impact to predict tumor existence. Manual segmentation of a …

In response to the growing importance of geospatial data, its analysis including semantic
segmentation becomes an increasingly popular task in computer vision today. Convolutional …

The traditional watershed algorithm has the disadvantage of over-segmentation and
interference with an image by reflected light. We propose an improved watershed color …

Computer aided diagnosis (CAD) of biomedical images assists physicians for a fast
facilitated tissue characterization. A scheme based on combining fuzzy logic (FL) and deep …

Nine previously proposed segmentation evaluation metrics, targeting medical relevance,
accounting for holes, and added regions or differentiating over-and under-segmentation …

Breast cancer is the second most common prevalent type of cancer found in women around
the world. Early detection and screening of individuals can be beneficial in hel** to bring …