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Autonomous driving has long faced a challenge with public acceptance due to the lack of explainability in the decision-making process. …

Large Language Models (LLMs) have shown promise in the autonomous driving sector, particularly in generalization and interpretability. …

Motivated by the impact of large-scale datasets on ML systems we present the largest self-driving dataset for motion prediction to …

The present invention provides a method of generating a robust global map using a plurality of limited field-of-view cameras to capture …

In this work, we present a simple end-to-end trainable machine learning system capable of realistically simulating driving experiences. …

We investigate what grade of sensor data is required for training an imitation-learning-based AV planner on human expert demonstration. …

Mixed reality (MR) is a powerful interactive technology for new types of user experience. We present a semantic-based interactive MR …

We present a novel self-supervised framework for monocular image depth learning and confidence estimation. Our framework reduces the …

Surgical smoke removal algorithms can improve the quality of intra-operative imaging and reduce hazards in image-guided surgery, a …

Background and objective: While Minimally Invasive Surgery (MIS) offers considerable benefits to patients, it also imposes big …