IEEE

Applying Machine Learning on Big Data With Apache Spark

Abstract: The exponential growth of data in the digital age has necessitated the development of frameworks capable of efficiently handling and processing vast datasets. This paper explores the ...
IEEE

Enhanced Local and Global Learning for Rotation-Invariant Point Cloud Representation

Abstract: Various studies have been undertaken to learn point cloud representations that are both discriminative and robust. However, most of them suffer from rotation disturbance and insufficient ...
IEEE

Clutter Detection in Automotive Radar Point Clouds Based on Deep Learning with Self-attention

Abstract: As radar can directly provide the velocity of the targets in autonomous driving and is known for the robustness against adverse weather conditions, it plays an important role in contrast to ...
IEEE

Enhanced P-Type Control: Indirect Adaptive Learning From Set-Point Updates

Abstract: In this article, an indirect adaptive iterative learning control (iAILC) scheme is proposed for both linear and nonlinear systems to enhance the P-type controller by learning from set points ...
IEEE

DA-Net: Density-Adaptive Downsampling Network for Point Cloud Classification via End-to-End Learning

Abstract: Since a point cloud might contain large quantities of points in practical scenarios, it is desirable to perform downsampling before point cloud analysis. Classic downsampling strategies, ...
IEEE

Learning Point Cloud Completion without Complete Point Clouds: A Pose-Aware Approach

Abstract: Point cloud completion is to restore complete 3D scenes and objects from incomplete observations or limited sensor data. Existing fully-supervised methods rely on paired datasets of ...
IEEE

Deep Learning Based Point Cloud Processing Techniques

Abstract: In this study, deep learning techniques and algorithms used in point cloud processing have been analysed. Methods, technical properties and algorithms developed for 3D Object Classification ...
IEEE

Point Cloud Denoising using Deep Learning

Abstract: The emergence of uncontrollable noise from diverse sources possess several difficulties in scanning 3D objects. In the case of animals in the wild this is especially hard to manage since ...
IEEE

Contrastive Learning for Joint Normal Estimation and Point Cloud Filtering

Abstract: Point cloud filtering and normal estimation are two fundamental research problems in the 3D field. Existing methods usually perform normal estimation and filtering separately and often show ...
IEEE

Detecting Java Compiled Malware using Machine Learning Techniques

Abstract: Malicious software using Java Language in order to implement the attack evolved rapidly in the past years. Initially we were used to find malicious Applets and exploitation methods to escape ...
IEEE

Weakly Supervised Learning for Point Cloud Semantic Segmentation With Dual Teacher

Abstract: Point cloud semantic segmentation has achieved considerable progress in the past decade. To alleviate expensive data annotation efforts, weakly supervised learning methods are preferable, ...