IEEE

An Efficient Compute-in-Memory based Accelerator for Point-based Point Cloud Neural Networks

Abstract: Point-based point cloud neural networks (PNNs) have shown remarkable accuracy in various applications. However, the performance of PNNs is usually limited on resource-constrained edge ...
IEEE

Online Network DoS/DDoS Detection: Sampling, Change Point Detection, and Machine Learning Methods

Abstract: Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks continue to pose significant threats to networked systems, causing disruptions that can lead to substantial financial ...
IEEE

LPRnet: A Self-Supervised Registration Network for LiDAR and Photogrammetric Point Clouds

Abstract: LiDAR and photogrammetry are active and passive remote sensing techniques for point cloud acquisition, respectively, offering complementary advantages and heterogeneous. Due to the ...
IEEE

Energy Conservation in Passive Optical Networks: A Tutorial and Survey

Abstract: The Passive Optical Network (PON) has been evolving continuously in terms of architecture and capacity to keep up with the demand for high-speed Internet access in the access network segment ...
IEEE

LighTN: Light-Weight Transformer Network for Performance-Overhead Tradeoff in Point Cloud Downsampling

Abstract: Downsampling is a crucial task for processing large scale and/or dense point clouds with limited resources. Owing to the development of deep learning, approaches of task-oriented point cloud ...
IEEE

VOJA-Net: Vector-Offset Joint Attention Network for ICESat-2 Point Cloud Data Denoising

Abstract: The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) is equipped with a new type of photon-counting laser altimetry system, demonstrating significant potential for global mapping.
Hacker

How the OSI and TCP/IP Models Power Modern Computer Networks

Engineer with 5+ years of experience at AWS. I write about various topics to rid myself of my imposter syndrome. Engineer with 5+ years of experience at AWS. I write about various topics to rid myself ...
IEEE

Dynamic Hypergraph Convolutional Network for No-Reference Point Cloud Quality Assessment

Abstract: With the rapid advancement of three-dimensional (3D) sensing technology, point cloud has emerged as one of the most important approaches for representing 3D data. However, quality ...
IEEE

No-Reference Point Cloud Quality Assessment via Graph Convolutional Network

Abstract: Three-dimensional (3D) point cloud, as an emerging visual media format, is increasingly favored by consumers as it can provide more realistic visual information than two-dimensional (2D) ...
IEEE

DeepBHMR: Learning Bidirectional Hybrid Mixture Models for Generalized Global Rigid Point Set Registration in Computer-Assisted Orthopedic Surgery

Abstract: This paper presents a novel robust and accurate normal-assisted learning-based rigid point set registration approach, i.e., Deep Bi-directional Hybrid Mixture Registration (DeepBHMR), where ...
IEEE

AdverseNet: A LiDAR Point Cloud Denoising Network for Autonomous Driving in Rainy, Snowy, and Foggy Weather

Abstract: In the field of autonomous driving, a pressing issue is how to enable LiDAR to accurately perceive the 3-D environment around the vehicle without being affected by rain, snow, and fog.
IEEE

Modeling 3D Cardiac Contraction and Relaxation With Point Cloud Deformation Networks

Abstract: Global single-valued biomarkers, such as ejection fraction, are widely used in clinical practice to assess cardiac function. However, they only approximate the heart's true 3D deformation ...