IEEE

Kinematic Recurrent Neural Network–Based Hybrid Calibration for Serial Manipulators

Abstract: This paper proposes a hybrid kinematic calibration framework for serial robotic manipulators that integrates analytical parameter identification with data-driven residual learning. First, ...
Journal of Medical Internet Research

Developing and Validating a Machine Learning Algorithm to Predict the Risk of Incident Opioid Use Disorder Among OneFlorida+ Patients: Prognostic Modeling Study

Using the GBM algorithm to predict the subsequent 3-month OUD risk, the top decile subgroup had a positive predictive value of 3.26%, a negative predictive value of 99.8%, and a number needed to ...
IEEE

Channel Prediction Using Deep Recurrent Neural Network With EVT-Based Adaptive Quantile Loss Function

Abstract: Ultra-reliable low latency communication (URLLC) systems are pivotal for applications demanding high reliability and low latency, such as autonomous vehicles. In such contexts, channel ...