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

Cross-Modality Feature Aggregation for Cross-Domain Point Cloud Representation Learning

Abstract: Existing methods for learning 3D point cloud representation often use a single dataset-specific training and testing approach, leading to performance drops due to significant domain shifts ...
IEEE

Dual-Neighborhood Feature Aggregation Network for Point Cloud Semantic Segmentation

Abstract: Neighborhood construction plays a key role in point cloud processing. However, existing models only use a single neighborhood construction method to extract neighborhood features, which ...
IEEE

DCNet: Large-Scale Point Cloud Semantic Segmentation With Discriminative and Efficient Feature Aggregation

Abstract: The point cloud feature aggregation, which learns discriminative features from the disordered points, plays a key role for large-scale point cloud semantic segmentation. Most previous ...
IEEE

Full Point Encoding for Local Feature Aggregation in 3-D Point Clouds

Abstract: Point cloud processing methods exploit local point features and global context through aggregation which does not explicitly model the internal correlations between local and global features ...
IEEE

Neighborhood Spatial Aggregation MC Dropout for Efficient Uncertainty-Aware Semantic Segmentation in Point Clouds

Abstract: Uncertainty-aware semantic segmentation of the point clouds includes predictive uncertainty estimation and uncertainty-guided model optimization. One key challenge in the task is the ...
IEEE

Towards Privacy-Preserving and Error-Tolerant Wireless Federated Learning: Fixed-Point Model Aggregation with Differential Privacy Guarantees

Abstract: This paper presents a novel approach for wireless federated learning (WFL) that, for the first time, enables the aggregation of local models with mild to moderate errors under practical ...