On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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4 results for “drone-based”

Multi-view Drone-based Geo-localization via Style and Spatial Alignmentcs.CV

A new method for drone-based geo-localization using style and spatial alignment.

problem Geo-localization of drone-view images with satellite-view images using pre-annotated GPS tags.

method Orientation-based method to align patterns, new branch to extract aligned partial features, style alignment strategy.

result The proposed method outperforms state-of-the-art alternatives in geo-localization accuracy.

geo-localization drone multi-view satellite style alignment

2020-06-23abs ↗pdf ↗

CitySim: A Drone-Based Vehicle Trajectory Dataset for Safety Oriented Research and Digital Twinscs.CV

CitySim dataset captures vehicle trajectories for safety research.

problem Lack of fine-grain vehicle trajectories for safety-oriented research.

method Five-step procedure: video stabilization, object filtering, stitching, detection, and error filtering.

result CitySim dataset improves safety evaluations and facilitates digital-twin research.

CitySim drone-based vehicle trajectories safety research digital twins

2022-08-23abs ↗pdf ↗

Trajectory Poisson multi-Bernoulli mixture filter for traffic monitoring using a dronecs.CV

A drone-based MOT algorithm tracks vehicles using neural network detections and TPMBM filter.

problem Tracking multiple vehicles from drone-mounted cameras.

method Neural network for object detection, TPMBM filter for trajectory estimation, von-Mises Fisher distribution for DOA.

result TPMBM filter optimally estimates vehicle trajectories.

drone traffic monitoring multi-object tracking TPMBM filter neural network

2023-06-29abs ↗pdf ↗

Meta-Reinforcement Learning for Trajectory Design in Wireless UAV Networkscs.LG

Meta-learning improves drone trajectory design for dynamic wireless networks.

problem Designing optimal trajectories for energy-constrained drones in dynamic network environments.

method Proposes a meta-learning algorithm to adaptively tune a reinforcement learning solution for trajectory design.

result Meta-tuned RL yields faster convergence and improved communication performance compared to baseline algorithms.

meta-reinforcement learning wireless drone networks trajectory design dynamic environments reinforcement learning

2020-05-25abs ↗pdf ↗