IEEE

3D point cloud robust sampling method based on aggregation rate

Abstract: Effective sampling plays a critical role in the preprocessing of 3D point cloud data, directly impacting the performance of downstream models. Traditional Farthest Point Sampling (FPS) ...
GitHub

Eclipse Paho Java Client

The Paho Java Client is an MQTT client library written in Java for developing applications that run on the JVM or other Java compatible platforms such as Android The Paho Java Client provides two APIs ...
IEEE

HCNet: Hierarchical Feature Aggregation and Cross-Modal Feature Alignment for Remote Sensing Image Captioning

Abstract: Remote sensing image captioning (RSIC) aims to describe the crucial objects from remote sensing images in the form of natural language. The inefficient utilization of object texture and ...
IEEE

Joint Adaptive Aggregation and Resource Allocation for Hierarchical Federated Learning Systems Based on Edge-Cloud Collaboration

Abstract: Hierarchical federated learning shows excellent potential for communication-computation trade-offs and reliable data privacy protection by introducing edge-cloud collaboration. Considering ...
IEEE

CPFedAvg: Enhancing Hierarchical Federated Learning via Optimized Local Aggregation and Parameter Mixing

Abstract: Hierarchical federated learning (HFL) improves the scalability and efficiency of traditional federated learning (FL) by incorporating a hierarchical topology into the FL framework. In a ...
IEEE

Multistage Particle Swarm Optimization for Heterogeneous Multipoint Dynamic Aggregation

Abstract: Multipoint dynamic aggregation (MPDA) is a multirobot task allocation problem, which requires the collaborative scheduling of multiple robots to complete time-varying tasks distributed on a ...
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

Byzantine Robust Aggregation in Federated Distillation with Adversaries

Abstract: Federated learning empowers privacy-preserving, multi-party secure model training without the necessity of sharing raw data. In recent years, knowledge distillation has emerged as a ...