Results 181 to 190 of about 2,077 (255)
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
The study on the relationship between perceived value, satisfaction, and tourist loyalty at industrial heritage sites. [PDF]
Qiu N, Li H, Pan C, Wu J, Guo J.
europepmc +1 more source
Pak Biawak, a necrobot, embodies an unusual fusion of biology and robotics. Designed to repurpose natural structures after death, it challenges conventional boundaries between nature and engineering. Its movements are precise yet unsettling, raising questions about sustainability, ethics, and the untapped potential of biointegrated machines.
Leo Foulds +2 more
wiley +1 more source
Exploring the mechanism by which tourists' perceived value influences revisit intention in sustainable gardens: A case study of KICG-sustainable garden, Shanghai. [PDF]
Chen J, Chen G.
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
Do the interpersonal effects of gamified online destination websites better stimulate tourists' travel intentions? [PDF]
Wang H, Qu M, Liu Y, Li W.
europepmc +1 more source
Push and pull factors as determinants of destination loyalty
M. I. Prete +5 more
openaire +2 more sources
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
Strategic Management of Low Carbon Travel in Longevity Tourism Evidence from Thailand. [PDF]
Madhyamapurush W.
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

