Current point cloud registration methods are mainly based on local geometric information and usually ignore the semantic information contained in the scenes. In this article, we treat the point cloud ...

Graph signal processing is an emerging field in which traditional signal processing tools from regular Euclidean domain are adapted for use in irregular domains such as graphs. This paper demonstrates ...

Change point detection in dynamic networks aims to detect the points of sudden change or abnormal events within the network. It has garnered substantial interest from researchers due to its potential ...

NEW DELHI, 12 Jul: Seconds before Air India flight 171 crashed while ascending from Ahmedabad, the fuel control switches of both its engines were cut off, a ...

Many health problems persisted up to 3 years post-discharge, with self-reported fatigue and cognitive problems worsening in the third year. PEM was common, and linked to a more severe phenotype of ...

Probabilistic path models have significantly improved generative tasks in computer vision. Researchers use diffusion model as 3D pretrained decoder, learning representation by predicting noise.

The rapidly evolving Industrial Internet of Things (IIoT) is driving the transition from conventional manufacturing to intelligent manufacturing. Intelligent shop scheduling, as one of the essential ...

Electroencephalography (EEG) signals record the electrical activity of the brain and have significant applications in neuroscience and medicine. However, accurately reconstructing EEG signals has been ...

In this paper, we propose FG-SAT, the first end-to-end method for encrypted traffic analysis under environment shifts. We propose a key abstraction, the Flow Graph, to represent flow internal ...

With rapid urbanization and technological advancements, increasing population density has posed significant challenges for urban traffic management. Traffic flow forecasting is essential for ...