Florida’s coral reefs are under siege. Since 2014, Stony Coral Tissue Loss Disease (SCTLD) has spread rapidly across the Florida Reef Tract and Caribbean, killing vast numbers of reef-building corals ...

In organelle imaging, segmentation aims to accurately delineate pixels or voxels corresponding to target organelles from background, noise, and other cellular structures in microscopy images, thereby ...

Aiming at the problems of intensity inhomogeneity, boundary blurring and noise interference in the segmentation of three-dimensional volume data (such as medical images and industrial CT data). In ...

Abstract: Deep convolutional neural networks (CNN) have recently achieved superior performance at the task of medical image segmentation compared to classic models. However, training a generalizable ...

With constant growth of civilization and modernization of cities all across the world since past few centuries smart traffic management of vehicles is one of the most sorted after problem by research ...

Abstract: Convolutional neural networks (CNNs) have achieved state-of-the-art performance for automatic medical image segmentation. However, they have not demonstrated sufficiently accurate and robust ...

An accurate three-dimensional (3D) segmentation of the maxillary sinus is crucial for multiple diagnostic and treatment applications. Yet, it is challenging and time-consuming when manually performed ...

Histology is key to understand physiology, development, growth and even reproduction of extinct animals. However, the identification and interpretation of certain structures, such as osteons, ...

Convolutional neural networks (CNN) have enabled significant improvements in pedestrian detection owing to the strong representation ability of the CNN features. However, it is generally difficult to ...