Paper Citation Record · LEDGER

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery

As of 8 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2506.03114.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.03114 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:10:10.691477Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

26 of 26 outbound references displayed

verified exact1
verified fuzzy17
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 64703b5e-b19e-49f5-989e-885513f6178e · outbound

This paper cites Accurate delineation of individual tree crowns in tropical forests from aerial rgb imagery using mask r-cnn.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Accurate delineation of individual tree crowns in tropical forests from aerial rgb imagery using mask r-cnn

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:10:13.900851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b6f563dd-e5d2-4029-99d9-7b008ccf642a · outbound

This paper cites Depth Any Canopy: Leveraging Depth Foundation Models for Canopy Height Estimation.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Depth Any Canopy: Leveraging Depth Foundation Models for Canopy Height Estimation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T11:10:08.675436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f82efe7-020e-41db-bd4e-769b1fe8b01a · outbound

This paper cites Mechanisms of forest resilience.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Mechanisms of forest resilience

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:10:13.740002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation be230a9f-011f-4abe-877c-8b9e1d75f6a4 · outbound

This paper cites Remote sensing in forestry: current challenges, considerations and directions.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Remote sensing in forestry: current challenges, considerations and directions

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:10:13.552899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4a9841c4-d146-4739-89b0-32bf3eacc31e · outbound

This paper cites Emerging signals of declining forest resilience under climate change.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Emerging signals of declining forest resilience under climate change

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:10:13.396405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a482cd45-873e-4bc9-a4b0-85f89a6b551d · outbound

This paper cites Automated detection of conifer seedlings in drone imagery using convolutional neural networks.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Automated detection of conifer seedlings in drone imagery using convolutional neural networks

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:10:13.221682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 50840c38-089e-4e36-9deb-a74458a4dfb2 · outbound

This paper cites Tree crown detection and delineation in a temperate deciduous forest from uav rgb imagery using deep learning approaches: Effects of spatial resolution and species characteristics.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Tree crown detection and delineation in a temperate deciduous forest from uav rgb imagery using deep learning approaches: Effects of spatial resolution and species characteristics

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:10:13.081918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e9b90eee-502d-4aaa-b2f0-fe95d92fc189 · outbound

This paper cites No more training: Sam’s zero-shot transfer capabilities for cost-efficient medical image segmentation.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery No more training: Sam’s zero-shot transfer capabilities for cost-efficient medical image segmentation

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:10:12.931624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0336df46-bf32-445d-8225-93081535b6ef · outbound

This paper cites Mask r-cnn.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Mask r-cnn

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:10:12.789826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 050bfeae-f5ec-4a74-adb8-be673a1998ac · outbound

This paper cites Masked autoencoders are scalable vision learners.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Masked autoencoders are scalable vision learners

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T11:10:09.329421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4bbb4778-7ee2-4abf-977a-dc67bb8209f3 · outbound

This paper cites Machine learning based wildfire susceptibility mapping using remotely sensed fire data and gis: A case study of adana and mersin provinces, turkey.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Machine learning based wildfire susceptibility mapping using remotely sensed fire data and gis: A case study of adana and mersin provinces, turkey

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:10:12.601472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 988efad2-b91c-4b08-b027-49960fc77f8c · outbound

This paper cites Segment anything.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Segment anything

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:10:12.386103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9eb81e93-1d5c-4a7f-b452-5a659784731d · outbound

This paper cites Applications in remote sensing to forest ecology and management.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Applications in remote sensing to forest ecology and management

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:10:12.216161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 426856ac-2082-4f19-95eb-3bbfce9d9a98 · outbound

This paper cites Focal Loss for Dense Object Detection.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Focal Loss for Dense Object Detection

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T11:10:09.599970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b824249-b047-4dd1-9b63-c07cabf37feb · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery SAM 2: Segment Anything in Images and Videos

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T11:10:09.703935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77b54fda-1fc7-4f3f-94d8-dee2ffe694f6 · outbound

This paper cites Hiera: A hierarchical vision transformer without the bells-and-whistles.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Hiera: A hierarchical vision transformer without the bells-and-whistles

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:10:12.076040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ec83f2e0-e1ed-4f32-9505-b8ea30e89946 · outbound

This paper cites Imputation of individual longleaf pine (pinus palustris mill.) tree attributes from field and lidar data.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Imputation of individual longleaf pine (pinus palustris mill.) tree attributes from field and lidar data

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:10:11.944626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation da625f82-af2c-4c6c-936c-a07c345f9a37 · outbound

This paper cites Attention is all you need.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Attention is all you need

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T11:10:09.954407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2367706-1aa5-4a70-959d-3535129c0ab2 · outbound

This paper cites Individual tree-crown detection in rgb imagery using semi-supervised deep learning neural networks.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Individual tree-crown detection in rgb imagery using semi-supervised deep learning neural networks

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:10:11.780272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b4bf0dde-902c-4cbc-b5bc-3a0713237051 · outbound

This paper cites Deepforest: A python package for rgb deep learning tree crown delineation.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Deepforest: A python package for rgb deep learning tree crown delineation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:10:11.566934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 292a61b0-b283-4a9b-b97e-d73f522eae88 · outbound

This paper cites A remote sensing derived data set of 100 million individual tree crowns for the national ecological observatory network.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery A remote sensing derived data set of 100 million individual tree crowns for the national ecological observatory network

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:10:11.388485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a907aaf3-8747-42c4-9be3-a9991d6b89d0 · outbound

This paper cites Optimizing aerial imagery collection and processing parameters for drone-based individual tree mapping in structurally complex conifer forests.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Optimizing aerial imagery collection and processing parameters for drone-based individual tree mapping in structurally complex conifer forests

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:10:11.209697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 733d879b-6284-474a-a31a-f43ec150dfdc · outbound

This paper cites write newline.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery write newline

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T11:10:10.434013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29c64473-e6ad-40fc-9c52-2c17fb5b99a7 · outbound

This paper cites @esa (Ref.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery @esa (Ref

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T11:10:10.533014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d86ded6e-04d0-451e-8627-5b618a978c62 · outbound

This paper cites an unresolved cited work.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery Unresolved cited work

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T11:10:10.625222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b5d5394-4bde-4471-b8ef-c2dd074e702c · outbound

This paper cites c a1Y-X )8 KY5 ׷ z!q1J_˨ =r?x ύ_m= S7 |ʪV ר GYt ,mw1 : sH ;ksF#L-: Ƴ). <c)r<͈ i??B|Ϸ= ad 4B75 K=.

Zero-Shot Tree Detection and Segmentation from Aerial Forest Imagery c a1Y-X )8 KY5 ׷ z!q1J_˨ =r?x ύ_m= S7 |ʪV ר GYt ,mw1 : sH ;ksF#L-: Ƴ). <c)r<͈ i??B|Ϸ= ad 4B75 K=

Reference 26

Resolution: verified exact; raw_fallback, observed 2026-08-07T11:10:10.981967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

No inbound Pith citation observations are available.