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

Toward Visual Interaction: Hand Segmentation by Combining 3-D Graph Deep Learning and Laser Point Cloud for Intelligent Rehabilitation

Abstract: Against the backdrop of the increasing trend of aging population in China and even globally, the demand for hand function rehabilitation is growing day by day, and human-machine interaction ...
IEEE

AUV Path Planning and Object Tracking Algorithm Based on Reinforcement Learning Under Point Cloud Observation

Abstract: Autonomous underwater vehicles (AUV) play an important role in the process of human exploration of the ocean. However, the existing AUV control methods are faced with the problem of ...
IEEE

Learning-Based Reflection-Aware Virtual Point Removal for Large-Scale 3D Point Clouds

Abstract: 3D point clouds are widely used for robot perception and navigation. LiDAR sensors can provide large scale 3D point clouds (LS3DPC) with a certain level of accuracy in common environment.
GitHub

Android Studio Tutorials: Java Edition

Learn how to make simple apps in Android Studio. Android Studio Tutorials: Java Edition provides practical examples and complete source code to help you build your first Android application using ...
IEEE

Class Incremental Learning With Less Forgetting Direction and Equilibrium Point

Abstract: Catastrophic forgetting is the core problem of class incremental learning (CIL). Existing work mainly adopts memory replay, knowledge distillation, and dynamic architecture to alleviate this ...
IEEE

PCDNF: Revisiting Learning-Based Point Cloud Denoising via Joint Normal Filtering

Abstract: Point cloud denoising is a fundamental and challenging problem in geometry processing. Existing methods typically involve direct denoising of noisy input or filtering raw normals followed by ...
IEEE

Transitioning From Federated Learning to Quantum Federated Learning in Internet of Things: A Comprehensive Survey

Abstract: Quantum Federated Learning (QFL) recently becomes a promising approach with the potential to revolutionize Machine Learning (ML). It merges the established strengths of classical Federated ...
IEEE

PointOBB: Learning Oriented Object Detection via Single Point Supervision

Abstract: Single point-supervised object detection is gaining attention due to its cost-effectiveness. However, existing approaches focus on generating horizontal bounding boxes (HBBs) while ignoring ...
IEEE

PointWavelet: Learning in Spectral Domain for 3-D Point Cloud Analysis

Abstract: With recent success of deep learning in 2-D visual recognition, deep-learning-based 3-D point cloud analysis has received increasing attention from the community, especially due to the rapid ...
IEEE

SphereNet: Learning a Noise-Robust and General Descriptor for Point Cloud Registration

Abstract: Point cloud registration aims to estimate a transformation that aligns point clouds collected from different perspectives. In learning-based point cloud registration, a robust descriptor is ...
InfoQ

Autonomous Big Data Optimization: Multi-Agent Reinforcement Learning to Achieve Self-Tuning Apache Spark

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...