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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: It is shown that the modernized Nyquist-Shannon theorem, which establishes the theoretical limit for the amount of information that can be obtained based on the analysis of a wave field ...
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 ...
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: This study explores an innovative approach to enhancing personalized learning through a negative sampling-optimized pedagogical recommendation model. The proposed methodology integrates ...
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: 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: Recent advancements in lidar technology have led to improved point cloud resolution as well as the generation of 360° low-resolution images by encoding depth, reflectivity, or near-infrared ...
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: In this article, we use methods from fixed point theory to examine a Lambda policy iteration with a randomization algorithm mappings that satisfy the Kannan contraction condition. As shown ...
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