Author name: Ben Fisher

In a significant stride towards enhancing brain tumor diagnosis, researchers have developed a novel hybrid deep learning framework that promises to revolutionize medical imaging analysis. The model, dubbed CVAE-UNETR-ResNet50-VGG16, is the brainchild

In a significant stride towards enhancing the safety and efficiency of maritime structures, researchers have developed a novel approach combining numerical simulations and machine learning to evaluate the ballistic performance of aluminum structures.

In a significant stride towards greener inland shipping, researchers have developed novel models to optimize operations for LNG-fuelled liner ships, addressing the unique challenges of inland waterways. The study, led by De-Chang Li from the Ship Tra

In the vast and complex world of maritime science, understanding the behavior of particles in water is crucial for a range of applications, from sediment transport to the design of marine structures. A recent study published in the Journal of Marine

In the ever-fluctuating world of maritime shipping, where fuel prices and carbon taxes can swing like a pendulum, making strategic decisions about fleet deployment and sailing speeds is no easy feat. Enter Weilin Sun, a researcher from the School of

In the vast expanse of the open sea, keeping an eye on maneuvering ships is a critical task for maritime surveillance. However, the images captured by Synthetic Aperture Radar (SAR) often show these ships blurred, making it tough to detect and recogn

In the ever-evolving world of maritime technology, a groundbreaking development has emerged from the labs of Nanjing University of Science and Technology. Researchers, led by Yuman Yuan from the Key Laboratory of Maritime Intelligent Cyberspace Techn

In a significant stride for maritime surveillance technology, researchers have introduced KuRALS, a novel radar dataset designed to enhance long-range detection of moving targets. This dataset, developed by Teng Li and his team at the Shenzhen Intern

In a significant stride towards enhancing traffic management systems, researchers have developed a novel approach that leverages the power of graph neural networks to estimate traffic states more accurately. This innovative method, published in the j