Floods are a devastating natural calamity that may seriously harm both infrastructure and
people. Accurate flood forecasts and control are essential to lessen these effects and …

Fuel cells have been regarded as promising power sources for cleaner energy production.
Despite their high theoretical efficiency, fuel cells are still challenged with their durability …

Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

In the past years, the computer vision domain has been profoundly changed by the advent of
deep learning algorithms and data science. The defect detection problem is of outmost …

Feather pecking (FP) is one of the primary welfare issues in commercial cage-free hen
houses as that can seriously reduce the well-being of birds and cause economic losses for …

Some of the major restaurants and grocery chains in the United States have pledged to buy
cage-free (CF) eggs only by 2025 or 2030. While CF house allows hens to perform more …

Train surface anomaly detection is an essential task in vision-based railway safety
inspection. Although existing deep learning methods show great potential, their anomaly …

Surface defect detection with machine learning has become an important tool in industries
and a large field of study for researchers or workers in recent years. It is necessary to have a …

Intelligent energy management in renewable-based power distribution applications, such as
microgrids, smart grids, smart buildings, and EV systems, is becoming increasingly important …

Aiming at the problems of low efficiency and poor accuracy in conventional surface defect
detection methods for aero-engine components, a surface defect detection model based on …