Researchers have developed a new algorithmic model that can improve predictions of cooling demand for greener buildings. This ...
Abstract: When object detection is carried out in settings with sparse and irregular data acquisition, conventional sequencing techniques that depend on continuous tracking or dense observations ...
The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...
The new law seeks to prevent retailers from ripping off consumers by using artificial intelligence and their personal data to charge them higher prices. By Tim Balk As New Yorkers scrolled, surfed and ...
ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...
Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability of decision ...
To address the issue of precisely identifying fishing grounds in vast sea areas, this study proposes a framework that includes a fishing behavior detection model and a fishing ground identification ...
Abstract: The spatio-temporal fusion technology can effectively solve the problem of missing time series data. However, existing algorithms often struggle to accurately capture surface feature changes ...
1 Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi'an, China 2 Department of Electrical and Computer ...
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