Results 211 to 220 of about 564,038 (269)
Model-Data Hybrid-Driven Wideband Channel Estimation for Beamspace Massive MIMO Systems. [PDF]
Nie Y, Ma Z, Jing L.
europepmc +1 more source
This study shows that a lightweight blackbox neural network provides a practical, cost‐effective solution for bidirectional process prediction in laser‐induced graphene (LIG) fabrication. Achieving high predictive performance with minimal overhead, the approach democratizes machine learning (ML) for resource‐limited environments.
Maxim Polomoshnov +3 more
wiley +1 more source
Dynamic Feature Fusion for Sparse Radar Detection: Motion-Centric BEV Learning with Adaptive Task Balancing. [PDF]
Sang Y +5 more
europepmc +1 more source
Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space
A quadruped robot masters dynamic jumps through constrained spaces with animal‐inspired moves and intelligent vision control. This hierarchical learning approach combines imitation of biological agility with real‐time trajectory planning. Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating ...
Zeren Luo +6 more
wiley +1 more source
RGB-conditioned frequency domain refinement for sparse-to-dense depth completion. [PDF]
Wang H, Tang Z, Pawara P, Chamchong R.
europepmc +1 more source
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar +8 more
wiley +1 more source
Influence of Uninformative Prior Distributions for MCMC Method on Estimating Variance Components in Generalizability Theory. [PDF]
Li G.
europepmc +1 more source
This work presents a robotic control method for human–robot collaborative assembly based on a biomechanics‐constrained digital human model. Reinforcement learning is used to generate physiologically plausible human motion trajectories, which are integrated into a virtual environment for robot control learning.
Bitao Yao +4 more
wiley +1 more source
Sparse Canonical Correlation Analysis for Multiple Measurements With Latent Trajectories. [PDF]
Senar N, Zwinderman AH, Hof MH.
europepmc +1 more source
Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki +2 more
wiley +1 more source

