Abstract: 3D Gaussian splatting (3DGS) suggests the use of explicit point-based 3D representations for high-fidelity novel view synthesis, with training and rendering speeds that are better than prior ...

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: The quantum Langevin equation of Ford, Kac, and Mazur is rederived and shown to be equivalent to an adjoint equation. This latter can be handled by means of van Kampen's cumulant expansion ...

Abstract: For three-dimensional (3D) imaging based on fringe projection profilometry (FPP), maximum fringe frequency selection and fringe frequencies allocation have a significant impact on the ...

Abstract: Point cloud-based 3D object detection technology provides precise information for detecting obstacles in front of trains. In rail transit scenarios, obstacles are usually located at a ...

Abstract: The incorporation of renewable energy sources (RESs) into power systems has significantly increased in recent years due to growing environmental, economic, and energy security concerns, ...

Abstract: Integration of distributed energy resources, such as photovoltaics, has expanded rapidly within power distribution networks in recent years. Existing management architectures face great ...

Abstract: Hyperspectral image denoising is crucial for accurate extraction of spectral information. However, current convolutional neural network (CNN)-based methods have inherent limitations, while ...

Abstract: Droop-controlled inverters reduce transient and steady-state frequency deviations (FDs) by providing frequency regulation (FR) power proportional to the FD during primary FR. However, with ...

Abstract: Photoacoustic endomicroscopy enables high-resolution imaging of deep microvasculature within the gastrointestinal wall using modulated laser pulses with point-by-point scanning. However, ...

Abstract: Reconstructing deformable anatomical structures from endoscopic videos is a pivotal and promising research topic that can enable advanced surgical applications and improve patient outcomes.

Abstract: Multivariate time series (MTS) anomaly detection is of great importance in both condition monitoring and malfunction identification within multi-sensor systems. Current MTS anomaly detection ...