Tree detection and counting have been performed using conventional methods or high
costly remote sensing data. In the past few years, deep learning techniques have gained …

Ship detection in synthetic aperture radar (SAR) images has attracted widespread attention
due to its significance and challenges. In recent years, numerous detectors based on deep …

Due to the rapid development of chip technology and deep learning revolution, many ship
detection frameworks for synthetic aperture radar (SAR) imagery based on convolutional …

To accurately extract various ground objects from polarimetric synthetic aperture radar
(PolSAR) images is a challenging research topic. The deep convolutional neural networks …

Deep learning algorithms have been proven to be a powerful tool in image and video
processing for security and surveillance operations. In a maritime environment, the fusion of …

Synthetic aperture radar (SAR) images have been used in many studies for ship detection
because they can be captured without being affected by time and weather. In recent years …

Abstract Point-of-care (POC) real-time polymerase chain reaction (PCR) has become one of
the most important technologies for many fields such as pathogen detection and water …

Detecting objects in computer vision is a challenging task, especially under varied weather
conditions such as rain, fog, snow, etc. which degrades the visibility, and illumination …

Deep learning has recently made an impressive advance in ship detection in Synthetic
Aperture Radar (SAR) images. Despite this advancement, conventional deep detection …

Maritime surveillance, characterized by high-volume data streams, necessitates effective
methods for the automatic extraction of meaningful information and accurate classification of …