SpinFlow parametrizes traffic phases with a latent spin vector and competitive-equilibrium mapping, then uses physics-regularized EM to invert the field from trajectories and localize transitions via a new PED metric.
A threshold selection method from gray-level histograms,
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
verdicts
UNVERDICTED 5representative citing papers
AssistDLO combines multi-view state estimation, visual assistance, and a geometry-aware shared-autonomy controller using control barrier functions for DLO teleoperation, with a user study showing that benefits depend on user expertise and object properties.
A dual-modal frame-event approach delivers real-time high-frame-rate binarization for silhouettes in dynamic scenes on CPU-only hardware by exploiting neuromorphic event data to reduce motion blur.
A data-adaptive probabilistic intensity remapping framework using Gaussian POVMs enables continuous, structure-preserving transformations in grayscale images with tunable sharpness and component resolution.
A 360 RGB video pipeline using SfM, Grounded SAM, and RANSAC achieves 5-9% median relative DBH error, only 2-4% above LiDAR, on 61 acquisitions of 43 trees.
citing papers explorer
-
SpinFlow: A Physics-Informed Spin Field Framework for Traffic Phase Inference and Transition Detection
SpinFlow parametrizes traffic phases with a latent spin vector and competitive-equilibrium mapping, then uses physics-regularized EM to invert the field from trajectories and localize transitions via a new PED metric.
-
AssistDLO: Assistive Teleoperation for Deformable Linear Object Manipulation
AssistDLO combines multi-view state estimation, visual assistance, and a geometry-aware shared-autonomy controller using control barrier functions for DLO teleoperation, with a user study showing that benefits depend on user expertise and object properties.
-
See Silhouettes in Motion with Neuromorphic Vision
A dual-modal frame-event approach delivers real-time high-frame-rate binarization for silhouettes in dynamic scenes on CPU-only hardware by exploiting neuromorphic event data to reduce motion blur.
-
Unsharp Measurement with Adaptive Gaussian POVMs for Quantum-Inspired Image Processing
A data-adaptive probabilistic intensity remapping framework using Gaussian POVMs enables continuous, structure-preserving transformations in grayscale images with tunable sharpness and component resolution.
-
Estimating the Diameter at Breast Height of Trees in a Forest from RGB
A 360 RGB video pipeline using SfM, Grounded SAM, and RANSAC achieves 5-9% median relative DBH error, only 2-4% above LiDAR, on 61 acquisitions of 43 trees.