Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T09:48:56.732951Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 84 of 84 outbound references and 0 inbound Pith citation observations for arXiv:2601.12500.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T09:48:56.732951Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
84 of 84 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 5dde05ce-c267-4f65-a043-3fe3194eae97 · outbound
Video Individual Counting and Tracking from Moving Drones: A Benchmark and Methods Integrated sensing and communication for low altitude econ- omy: Opportunities and challenges,
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Video Individual Counting and Tracking from Moving Drones: A Benchmark and Methods Unmanned aerial vehicles based low-altitude economy with lifecycle techno-economic-environmental analysis for sustainable and smart cities,
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Video Individual Counting and Tracking from Moving Drones: A Benchmark and Methods Low-altitude intelligent transportation: System architecture, infrastructure, and key technologies,
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Video Individual Counting and Tracking from Moving Drones: A Benchmark and Methods Rethinking counting and localization in crowds: A purely point-based framework,
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Video Individual Counting and Tracking from Moving Drones: A Benchmark and Methods Composition loss for counting, density map estimation and localization in dense crowds,
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Video Individual Counting and Tracking from Moving Drones: A Benchmark and Methods Single-image crowd counting via multi-column convolutional neural network,
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Video Individual Counting and Tracking from Moving Drones: A Benchmark and Methods Reducing spatial labeling redundancy for active semi-supervised crowd counting,
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