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Found 7 papers, 1 papers with code
Blending Data-Driven Priors in Dynamic Games
As intelligent robots like autonomous vehicles become increasingly deployed in the presence of people, the extent to which these systems should leverage model-based game-theoretic planners versus data-driven policies for safe, interaction-aware motion planning remains an open question.
Who Plays First? Optimizing the Order of Play in Stackelberg Games with Many Robots
To solve the problem, we introduce Branch and Play (B&P), an efficient and exact algorithm that provably converges to a socially optimal order of play and its Stackelberg equilibrium.
Introspective Planning: Guiding Language-Enabled Agents to Refine Their Own Uncertainty
Large language models (LLMs) exhibit advanced reasoning skills, enabling robots to comprehend natural language instructions and strategically plan high-level actions through proper grounding.
Deception Game: Closing the Safety-Learning Loop in Interactive Robot Autonomy
An outstanding challenge for the widespread deployment of robotic systems like autonomous vehicles is ensuring safe interaction with humans without sacrificing performance.
MAF-Net: Multiple attention-guided fusion network for fundus vascular image segmentation
To enrich contextual information for the loss of scene information compensation, an attention fusion mechanism that combines the channel attention with spatial attention mechanisms constructed by Transformer is employed to extract various features of blood vessels from retinal fundus images.
Novel coronavirus pneumonia lesion segmentation in CT images
Results: The performance of the proposed method was validated in experiments with a publicly available dataset.
Pixel-Wise Motion Deblurring of Thermal Videos
To address this problem, this paper formulates reversing the effect of thermal inertia at a single pixel as a Least Absolute Shrinkage and Selection Operator (LASSO) problem which we can solve rapidly using a quadratic programming solver.
