IEEE

HashPoint: Accelerated Point Searching and Sampling for Neural Rendering

Abstract: In this paper, we address the problem of efficient point searching and sampling for volume neural rendering. Within this realm, two typical approaches are employed: rasterization and ray ...
IEEE

On the Methods of Further Generalization of Nyquist–Shannon sampling theorem

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 ...
IEEE

A Quality-Aware Sampling Framework for Efficient 3D Point Cloud Transmission

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 ...
IEEE

Parameter Identification for Inverse Scattering Problem of Electrically Large Curved Surfaces

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 ...
IEEE

Innovative Negative Sampling and Natural Language Processing Approach for Optimizing Knowledge Point Recommendations in Personalized Learning

Abstract: This study explores an innovative approach to enhancing personalized learning through a negative sampling-optimized pedagogical recommendation model. The proposed methodology integrates ...
IEEE

SegSAM-3D: Integrating Semantic Point Prompts and Multi-Layer Feature Sampling in SAM for Medical Imaging Segmentation

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 ...
IEEE

Efficient Point Cloud Streaming via Curvature and Edge-Aware Sampling and Deep-Learning-Based Reconstruction

Abstract: Point clouds have emerged as a preferred representation for 3D information in various immersive applications. The delivery of high-quality point clouds demands a lot of bandwidth, which ...
IEEE

Learning-Based Sampling Method for Point Cloud Segmentation

Abstract: Light detection and ranging (LiDAR) has become one of the most important sensors in 3-D perception. With the advancement of sensor technology, the point cloud data generated by LiDAR have ...
IEEE

3D Facial Ethnicity Identification Using PointNet++ with Data Augmentation Based on Farthest Point Sampling

Abstract: Facial features vary among ethnic groups, and the analysis of facial shape is important in examining the similarity of these features. 3D facial point cloud data possesses diverse feature ...
IEEE

Investigating Lambda Policy Iteration with Randomization Using Kannan Fixed Point Theorem

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 ...
IEEE

A Digital Superresolution Method With Minimal Sensitivity to Shift Estimation Error

Abstract: Superresolution (SR) methods become essential when an undersampled low-resolution (LR) image is unable to provide accurate target detection. The estimation of an HR image from a single LR ...
IEEE

3D point cloud robust sampling method based on aggregation rate

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) ...