IEEE

Adaptive Federated Learning With Reinforcement Learning-Based Client Selection for Heterogeneous Environments

Abstract: This study introduces an Adaptive Federated Learning (AFL) framework designed to address the challenges of data heterogeneity, resource imbalance, and communication constraints in ...
IEEE

LFCNet: Deep Learning-Based LiDAR-Fisheye Camera Online Automatic Targetless Extrinsic Calibration

Abstract: This paper presents LFCNet, an end-to-end deep-learning framework for targetless extrinsic calibration between LiDAR and fisheye cameras. The method is specifically designed for autonomous ...
Frontiers

Interpretable machine learning models to predict survival in esophageal cancer: a study based on the SEER database and external validation in China

The final, formatted version of the article will be published soon. Objective:We developed interpretable machine learning(ML) models to predict the overall survival(OS) of esophageal cancer patients.