Abstract: Single-photon lidar detection data in applications can show different characteristics: sparse count data and strong noise count data with low signal-to-background ratio (SBR), making it ...
Abstract: Text data classification in social networks is a crucial task for various applications such as sentiment analysis, spam detection, and content moderation. This abstract presents an algorithm ...
Abstract: The truncated singular value decomposition and its various tensor generalizations have long offered a simple and practical mechanism for compressing data stored in 2D or higherorder tensors.
Abstract: Changes in lake water levels are closely related to climate change and can also reflect information about local human activities. Therefore, obtaining high temporal resolution time series of ...
Abstract: In light of the growing global concerns over energy and climate change, new energy vehicles are confronted with both opportunities and challenges posed by industrial structural ...
Abstract: This paper proposes an intelligent control algorithm for low-altitude targets that fuses data from multiple sensors, aiming to enhance the detection, recognition, and tracking capabilities ...
Placebo-adjusted mean weight loss of 16.3% (39 lbs) at 180 mg and 16.0% (37 lbs) at 240 mg at 44 weeks with no evidence of weight loss plateau in ACCESS II, demonstrating highest efficacy among oral ...
John Solly, a software engineer and former member of the so-called Department of Government Efficiency (DOGE), is the DOGE operative reportedly accused in a whistleblower complaint of telling ...
Abstract: Glaucoma, an irreversible neurodegenerative disorder, can lead to vision loss and blindness. Visual field (VF) tests are crucial for quantifying functional damage in glaucoma, but the tests ...
Abstract: Geosynchronous-Earth-orbit (GEO) synthetic aperture radar (SAR) is able to achieve targeted observation, thanks to its flexibility in antenna steering, while focusing GEO SAR data is ...
Abstract: Graph structure learning (GSL) has shown promise in various domains, but its potential impact on tabular data prediction remains underexplored. Traditional deep learning models for tabular ...