Abstract: Time series classification is an important task in time series data mining, and has attracted great interests and tremendous efforts during last decades. However, it remains a challenging ...
Abstract: In this monograph, the authors present an introduction to the framework of variational autoencoders (VAEs) that provides a principled method for jointly learning deep latent-variable models ...
Abstract: Vegetation is a key component of biodiversity and ecosystem stability. The normalized difference vegetation index (NDVI) is widely used to monitor the vegetation growth status. Timely ...
Abstract: Accurate pedestrian trajectory prediction is a crucial task for ensuring the safety of autonomous driving. However, most of the existing methods only model pedestrian trajectories in the ...
Book Abstract: Electrical Engineering/Electromagnetics Waves and Fields in Inhomogeneous Media A Volume in the IEEE Press Series on Electromagnetic Waves Donald G ...
Abstract: Offset-based representation has emerged as a promising approach for modeling semantic relations between pixels and object motion, demonstrating efficacy across various computer vision tasks.
Abstract: This study explores the potential of digital light processing to 3D print radioactive phantoms for high-resolution positron emission tomography (PET). Using a slightly modified desktop 3D ...
Abstract: At present, underwater robot self-localization methods mainly rely on inertial measurement unit (IMU) and Doppler velocity log (DVL) based dead reckoning (DR) and standard camera-based ...
Abstract: The Concept Bottleneck Model (CBM) is an interpretable neural network that leverages high-level concepts to explain model decisions and conduct human-machine interaction. However, in ...
Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=36 ...
Abstract: Effectively integrating the time-space-frequency information of multi-modal signals from armband sensor, including surface electromyogram (sEMG) and accelerometer data, is critical for ...
Abstract: Geostationary orbit (GEO) microwave sounding technology, which can continuously monitor Earth and intensively observe weather conditions such as strong convection, has unique advantages. An ...
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