The Internet of Underwater Things (IoUT) is an emerging communication ecosystem
developed for connecting underwater objects in maritime and underwater environments …

Semantic segmentation of urban scenes is an essential component in various applications
of autonomous driving. It makes great progress with the rise of deep learning technologies …

Online state of health (SOH) prediction of lithium‐ion batteries remains a very important
problem in assessing the safety and reliability of battery‐powered systems. Deep learning …

Coral reefs are home to a variety of species, and their preservation is a popular study area;
however, monitoring them is a significant challenge, for which the use of robots offers a …

To evaluate the performance of deep learning methods on the landslide susceptibility
mapping, five different convolutional neural networks (CNN)—AlexNet, Inception-v3 …

With increasing focus on Artificial Intelligence (AI) applications, Deep Neural Networks
(DNNs) have been successfully used in a number of application areas. As the number of …

Coral species detection underwater is a challenging problem. There are many cases when
even the experts (marine biologists) fail to recognize corals, hence limiting ground truth …

Underwater caves are challenging environments that are crucial for water resource
management, and for our understanding of hydro-geology and history. Mapping underwater …

Monitoring coral reef populations as part of environmental assessment is essential.
Recently, many marine science researchers are employing low-cost and power efficient …

In this paper, we propose a real-time deep learning approach for determining the 6D relative
pose of Autonomous Underwater Vehicles (AUV) from a single image. A team of …