Abstract: We propose an end-to-end attribute compression method for dense point clouds. The proposed method combines a frequency sampling module, an adaptive scale feature extraction module with ...
The Global Network of Isotopes in Precipitation (GNIP) is a worldwide isotope monitoring network of hydrogen and oxygen isotopes in precipitation, initiated in 1960 by the International Atomic Energy ...
Abstract: The large volume of data from the point cloud brings significant demands on network bandwidth. However, the current transmission framework only considers using lossy compression to control ...
Abstract: Driven by the increasing demand for accurate and efficient representation of 3D data in various domains, point cloud sampling has emerged as a pivotal research topic in 3D computer vision.
Abstract: Effective sampling plays a critical role in the preprocessing of 3D point cloud data, directly impacting the performance of downstream models. Traditional Farthest Point Sampling (FPS) ...
Abstract: Inverse scattering problems (ISPs) often suffer from severe ill-posedness and nonlinearity. In this article, a parameter identification method that determines the necessary conditions of ...
Abstract: Plant point cloud completion is essential for tasks like segmentation and surface reconstruction in plant phenotyping. Unlike the relatively simpler Computer-Aided Design models found in ...
Abstract: This study explores an innovative approach to enhancing personalized learning through a negative sampling-optimized pedagogical recommendation model. The proposed methodology integrates ...
Abstract: Accurate semantic segmentation of 3D point clouds is pivotal for comprehensive understanding and modeling of real-world environments. Unlike traditional 2D images, 3D point clouds offer ...
Abstract: To address the challenge of stem visual localization in tomato automated harvesting, this paper focuses on the failure modes encountered when a depth camera attempts to detect very thin ...
Abstract: Medical imaging segmentation, particularly in 3D, poses significant challenges related to accuracy and computational cost. Existing 2D prompt segmentation models, such as Segment Anything ...
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