Using Fast Classification of Static and Dynamic Environment for Improving Bayesian Occupancy Filter (BOF) and Tracking
type: Dataset
description: International audience
issued: 2026-06-04T01:40:49.629379
language: en
modified: 2026-06-04T01:40:49.629385
contact point: Organization
  fn: CCSD
keyword: conference-papers
keyword: infoeu-reposemanticsconferenceobject
landing page: In IEEE International Conference on Control, Automation, Robotics and Vision (ICARCV)

Using Fast Classification of Static and Dynamic Environment for Improving Bayesian Occupancy Filter (BOF) and Tracking
type: Distribution
format: HTML
issued: 2026-06-04T01:40:49.675552
modified: 2026-06-04T01:40:49.619740
access URL: https://inria.hal.science/hal-00757400

test_moissonnage_selune
type: Agent