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Found 7 papers, 3 papers with code
Investigating the Helpfulness of Word-Level Quality Estimation for Post-Editing Machine Translation Output
For helpful quality levels, a visualization reflecting the uncertainty of the QE model is preferred.
Looking for a better fit? An Incremental Learning Multimodal Object Referencing Framework adapting to Individual Drivers
The rapid advancement of the automotive industry towards automated and semi-automated vehicles has rendered traditional methods of vehicle interaction, such as touch-based and voice command systems, inadequate for a widening range of non-driving related tasks, such as referencing objects outside of the vehicle.
Toward a Surgeon-in-the-Loop Ophthalmic Robotic Apprentice using Reinforcement and Imitation Learning
Thus, we propose a simulation-based image-guided approach for surgeon-centered autonomous agents that can adapt to the individual surgeon's skill level and preferred surgical techniques during ophthalmic cataract surgery.
SynthoGestures: A Novel Framework for Synthetic Dynamic Hand Gesture Generation for Driving Scenarios
Creating a diverse and comprehensive dataset of hand gestures for dynamic human-machine interfaces in the automotive domain can be challenging and time-consuming.
Teach Me How to Learn: A Perspective Review towards User-centered Neuro-symbolic Learning for Robotic Surgical Systems
Recent advances in machine learning models allowed robots to identify objects on a perceptual nonsymbolic level (e. g., through sensor fusion and natural language understanding).
Integrating Artificial and Human Intelligence for Efficient Translation
Current advances in machine translation increase the need for translators to switch from traditional translation to post-editing of machine-translated text, a process that saves time and improves quality.
