IEEE

PI-Based Set-Point Learning Control for Batch Processes With Unknown Dynamics and Nonrepetitive Uncertainties

Abstract: For industrial batch processes with unknown dynamics subject to nonrepetitive initial conditions and disturbances, this article develops a novel adaptive data-driven set-point learning ...
IEEE

NeuPAN: Direct Point Robot Navigation With End-to-End Model-Based Learning

Abstract: Navigating a nonholonomic robot in a cluttered, unknown environment requires accurate perception and precise motion control for real-time collision avoidance. This article presents neural ...
IEEE

GS-PT: Exploiting 3D Gaussian Splatting for Comprehensive Point Cloud Understanding via Self-supervised Learning

Abstract: Self-supervised learning of point cloud aims to leverage unlabeled 3D data to learn meaningful representations without reliance on manual annotations. However, current approaches face ...
IEEE

Domain Adaptation on Point Clouds via Multi-Modal Representation Learning

Abstract: Enhancing cross-domain performance of 3D point cloud neural networks remains a formidable task due to subtle variations in feature distributions among datasets, limiting their ...
IEEE

Eliminating Rogue Access Point Attacks in IoT: A Deep Learning Approach With Physical-Layer Feature Purification and Device Identification

Abstract: Wi-Fi plays an essential role in various emerging Internet of Things (IoT) services and applications in smart cities and communities, such as IoT access, data transmission, and intelligent ...
IEEE

Image Understands Point Cloud: Weakly Supervised 3D Semantic Segmentation via Association Learning

Abstract: Weakly supervised point cloud semantic segmentation methods that require 1% or fewer labels with the aim of realizing almost the same performance as fully supervised approaches have recently ...
IEEE

SiT-MLP: A Simple MLP With Point-Wise Topology Feature Learning for Skeleton-Based Action Recognition

Abstract: Graph convolution networks (GCNs) have achieved remarkable performance in skeleton-based action recognition. However, previous GCN-based methods rely on elaborate human priors excessively ...
IEEE

Learning Rearrangement Manipulation via Scene Prediction in Point Cloud

Abstract: Predicting scene evolution conditioned on robotic actions is a vital technique in modeling robot manipulations. Previous studies have primarily focused on learning spatiotemporally ...
IEEE

Point-Based Weakly Supervised Deep Learning for Semantic Segmentation of Remote Sensing Images

Abstract: Weakly supervised semantic segmentation methods can effectively alleviate the problem of high cost and difficult access to annotation in traditional methods. Among these approaches, point ...
IEEE

Student-Led Tutorials Interactions and Learning in Electromagnetism

Abstract: Contribution: This study identifies the types of interaction that contribute to student learning with student-led tutorials (SLTs). The quality of these interactions include peer discussion, ...
GitHub

Apress/Learn-Java-Fundamentals

This repository accompanies Learn Java Fundamentals by Jeff Friesen (Apress, 2024). Download the files as a zip using the green button, or clone the repository to your machine using Git.