By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

This important study presents a new method for longitudinally tracking cells in two-photon imaging data that addresses the specific challenges of imaging neurons in the developing cortex. It provides ...

A professor has helped create a powerful new algorithm that uncovers hidden patterns in complex networks, with potential uses in fraud detection, biology and knowledge discovery.

Aiming at the problem that existing human motion detection algorithms have low recognition accuracy on complex backgrounds, this paper proposes a human action recognition algorithm based on improved ...

From the success and accuracy graphs, it is evident that the existing hyperspectral image sequence target localization algorithm, the HLT algorithm, and the proposed hyperspectral low altitude UAV ...

In this work, we propose 3DMOTFormer, a learned geometry-based 3D MOT framework building upon the transformer architecture. We use an Edge-Augmented Graph Transformer to reason on the track-detection ...

Road network graphs provide critical information for autonomous-vehicle applications, such as drivable areas that can be used for motion planning algorithms. To find road network graphs, manual ...

They’ve created an algorithm, described in a paper in Science Advances today, that they claim improves the detection capacity of earthquake monitoring networks in cities and other built-up areas.