Offshore wind turbines are subjected to highly-varying dynamic loadings and accelerated
material degradation, resulting in the need for structural health monitoring, which increases …

Justifiably, while big data is the primary interest of research and public discourse, it is
essential to acknowledge that small data remains prevalent. The same technological and …

With the increasing population of Industry 4.0, both AI and smart techniques have been
applied and become hotly discussed topics in industrial cyber-physical systems (CPS) …

The main challenge for fine-grained few-shot image classification is to learn feature
representations with higher inter-class and lower intra-class variations, with a mere few …

Spinal maladies are among the most common causes of pain and disability worldwide.
Imaging represents an important diagnostic procedure in spinal care. Imaging investigations …

The goal of few-shot fine-grained image classification (FSFGIC) is to distinguish subordinate-
level categories with subtle visual differences such as the species of bird and models of car …

Planktonic organisms including phyto-, zoo-, and mixoplankton are key components of
aquatic ecosystems and respond quickly to changes in the environment, therefore their …

In existing fault diagnosis methods, fault categories are generally coarse-grained, which
may result in failure to precisely identify fault details. Therefore, fine-grained fault diagnosis …

State-of-the-art deep learning systems (eg, ImageNet image classification) typically require
very large training sets to achieve high accuracies. Therefore, one of the grand challenges is …

In this work, we present MorphoCluster, a software tool for data-driven, fast, and accurate
annotation of large image data sets. While already having surpassed the annotation rate of …