Paper Citation Record · LEDGER

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging

As of 14 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 1 inbound Pith citation observation for arXiv:2506.05360.

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

pith.paper-citation-record.v1
2506.05360 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:36:14.633402Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T10:54:38.542810Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

verified exact4
verified fuzzy20
unresolved9
parse uncertain0
malformed identifier2
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 70cf61d0-334e-4047-94d5-c2a9148382f4 · outbound

This paper cites Scientific Reports15(1), 3655 (2025).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging Scientific Reports15(1), 3655 (2025)

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:19.960475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 502251d2-4c5b-4f15-8813-37797cd26efd · outbound

This paper cites IoT 1, 286–308 (2020).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging IoT 1, 286–308 (2020)

Reference 2

Resolution: verified exact; doi, observed 2026-08-07T14:36:15.636632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a4208714-2a11-4e5d-bd89-21e8f4083185 · outbound

This paper cites In: Proceedings of the IEEE conference on computer vision and pattern recognition.

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging In: Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T14:36:11.932083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a16695e-0f9d-4699-bc26-32ba6f791ec5 · outbound

This paper cites Diagnostics14, 785 (2024).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging Diagnostics14, 785 (2024)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:19.797068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 480b42bb-db64-4334-bb29-c913b560490f · outbound

This paper cites Applied Energy225, 332–345 (2018).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging Applied Energy225, 332–345 (2018)

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:19.602870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d6b53a34-0be7-4af5-bdbd-ef9606fcbd75 · outbound

This paper cites In: ECCV (2018).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging In: ECCV (2018)

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:19.423786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 083dde34-fa1a-4a0a-a74b-1451d7d38d08 · outbound

This paper cites In: Communications in Computer and Information Science, pp.

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging In: Communications in Computer and Information Science, pp

Reference 7

Resolution: verified exact; doi, observed 2026-08-07T14:36:15.404038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 79edd4a0-ef24-4349-aee9-a9a50dc329ec · outbound

This paper cites ACM Transactions on Sensor Networks17(2), 1–44 (2021).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging ACM Transactions on Sensor Networks17(2), 1–44 (2021)

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:19.173319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 56f2164f-dec1-4640-83e9-7fa0de59630c · outbound

This paper cites https://github.com/open-mmlab/mmsegmentation (2020).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging https://github.com/open-mmlab/mmsegmentation (2020)

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T14:36:12.537062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d82e4cbc-e99f-41c4-a5a2-962f2f36a88f · outbound

This paper cites Heliyon (2025).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging Heliyon (2025)

Reference 10

Resolution: verified exact; doi, observed 2026-08-07T14:36:15.171363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 28054769-0c39-4d17-91d8-3435dd45f57e · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:36:12.692668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ea99ca2-2292-4783-91b0-a3a75500b90f · outbound

This paper cites Sensors24(17), 5675 (2024).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging Sensors24(17), 5675 (2024)

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:19.009543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation df02da2b-47db-44d5-83e6-389ba43c3f3c · outbound

This paper cites IET Image Processing19(1), e13327 (2025).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging IET Image Processing19(1), e13327 (2025)

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:18.781204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6f2e94e7-fd9f-4503-b8a3-7706e7755425 · outbound

This paper cites com/products/g343 (2023), accessed: September 18, 2025.

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging com/products/g343 (2023), accessed: September 18, 2025

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:18.585241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 16ac0385-2e74-4969-9682-4d05554fea01 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:18.484848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4a1a7d92-25a5-490b-bfe0-1ced7d1b3674 · outbound

This paper cites Reviews in Analytical Chemistry (2023).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging Reviews in Analytical Chemistry (2023)

Reference 16

Resolution: verified exact; doi, observed 2026-08-07T14:36:14.983719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5a44ab6b-9987-48b5-a1e9-49538f1425e7 · outbound

This paper cites SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation.

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:36:13.173759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0254b6c-127e-46c5-b3bd-a535b5639546 · outbound

This paper cites LangGas: Introducing Language in Selective Zero-Shot Background Subtraction for Semi-Transparent Gas Leak Detection with a New Dataset.

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging LangGas: Introducing Language in Selective Zero-Shot Background Subtraction for Semi-Transparent Gas Leak Detection with a New Dataset

Reference 18

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T14:36:15.914697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1d649b3a-7b68-48ea-84e3-397c923ae769 · outbound

This paper cites Journal of Animal Science94, 570–570 (2016).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging Journal of Animal Science94, 570–570 (2016)

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:18.396753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 55fdeb17-16bc-47a9-bd0f-baf084e119a4 · outbound

This paper cites Advances in Neural Information Processing Systems37, 63441–63465 (2024).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging Advances in Neural Information Processing Systems37, 63441–63465 (2024)

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:18.210641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b3e28b1b-cb0a-4513-9c4d-8c807e3ee2c8 · outbound

This paper cites Swin Transformer: Hierarchical Vision Transformer using Shifted Windows.

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T14:36:13.511153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e907e96f-7111-42af-bea7-6f6b18328f8d · outbound

This paper cites Electronics and Communications in Japan (2023).https://doi.org/10.1002/ecj.

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging Electronics and Communications in Japan (2023).https://doi.org/10.1002/ecj

Reference 22

Resolution: malformed identifier; doi_truncated, observed 2026-08-07T14:36:14.827338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e8408f68-f84f-4aff-8997-b7060aa85647 · outbound

This paper cites Remote Sensing 11(6), 659 (2019).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging Remote Sensing 11(6), 659 (2019)

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:18.066629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a8cbc6ac-1edc-4eb1-a5c1-ff924b26327d · outbound

This paper cites gov/vital-signs/carbon-dioxide/ (2025), accessed: September 18, 2025.

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging gov/vital-signs/carbon-dioxide/ (2025), accessed: September 18, 2025

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:17.839227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bd362b97-1cd0-4572-b4b1-f3f78da83893 · outbound

This paper cites Molecules30(3), 650 (2025).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging Molecules30(3), 650 (2025)

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:17.660930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation da34e5d4-02a4-4cea-8b51-c72acf26a8ce · outbound

This paper cites IEEE Transactions on Intelligent Transportation Systems (2022).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging IEEE Transactions on Intelligent Transportation Systems (2022)

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:17.455103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 44b86ab5-d721-4aa6-ab26-73273a72239d · outbound

This paper cites Fast-SCNN: Fast Semantic Segmentation Network.

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging Fast-SCNN: Fast Semantic Segmentation Network

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T14:36:13.939751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53013300-bbe4-4be3-940a-f8c5b6f19da8 · outbound

This paper cites In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision.

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:17.217832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 720467cd-2921-4c14-b95e-622c36520e69 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:17.020055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5e4f47c4-b0cf-4c43-83de-0de1ec09df77 · outbound

This paper cites Unpublished (2019).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging Unpublished (2019)

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:16.779660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 35e4aa40-20f9-429c-879a-4ab345e3b8d6 · outbound

This paper cites ACS Sensors 6, 1536–1542 (2021).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging ACS Sensors 6, 1536–1542 (2021)

Reference 31

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T14:36:16.545242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f972082e-51d5-4035-91f5-8cc3d7a27e0d · outbound

This paper cites SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers.

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T14:36:14.302147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84fab626-d655-4032-8b39-0f2477f0cfc0 · outbound

This paper cites International Journal of Computer Vision pp.

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging International Journal of Computer Vision pp

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:16.332721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 47a3c636-1dfc-4cc0-baf7-8722f112f955 · outbound

This paper cites In: Proceedings of the IEEE conference on computer vision and pattern recognition.

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T14:36:14.491894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d379d845-6dc1-46e4-83b5-bd8b533c9f92 · outbound

This paper cites In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T14:36:14.542079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d8acd21-3671-4403-bb23-5c7f1de2893d · outbound

This paper cites Sensors 23(5), 2566 (2023).

CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging Sensors 23(5), 2566 (2023)

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:36:16.131268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

Observation f21aaeb5-8c65-440e-bf1e-295c53703c09 · inbound

FUME: Fused Unified Multi-Gas Emission Network for Livestock Rumen Acidosis Detection cites this paper.

FUME: Fused Unified Multi-Gas Emission Network for Livestock Rumen Acidosis Detection CarboFormer: A Lightweight Semantic Segmentation Architecture for Efficient Carbon Dioxide Detection Using Optical Gas Imaging

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T10:54:38.542810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.