Deep learning requires a large amount of data to perform well. However, the field of medical
image analysis suffers from a lack of sufficient data for training deep learning models …

The global community has recognized an increasing amount of pollutants entering oceans
and other water bodies as a severe environmental, economic, and social issue. In addition …

In make-to-order manufacturing workshops, accurate prediction value of production
progress (PP) is a significant reference index for dynamic optimisation of production process …

In the last 40 years, remote sensing technology has evolved, significantly advancing ocean
observation and catapulting its data into the big data era. How to efficiently and accurately …

In recent decades, eutrophication in inland and coastal waters (ICWs) has increased due to
anthropogenic activities and global warming, thus requiring timely monitoring. Compared …

Ship type classification of synthetic aperture radar imagery with convolution neural network
(CNN) has been faced with insufficient labeled datasets, unoptimized and noised …

Dense sea fog events are responsible for many traffic accidents and fatalities. Research has
demonstrated the difficulty in distinguishing sea fog from clouds. This study presents a sea …

Polar-orbiting satellites have been widely used for detecting sea fog because of their wide
coverage and high spatial and spectral resolution. FengYun-3D (FY-3D) is a Chinese …

In this paper, a data-driven transfer learning (TL) model for locating tropical cyclone (TC)
centers from satellite infrared images in the northwest Pacific is developed. A total of 2450 …

Sea fog detection with remote sensing images is a challenging task. Driven by the different
image characteristics between fog and other types of clouds, such as textures and colors, it …