Paper Citation Record · LEDGER

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting

As of 19 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2505.16513.

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

pith.paper-citation-record.v1
2505.16513 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:01:06.165592Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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 fuzzy22
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2efcb11e-f289-49f1-ac62-eabde6d6a7c6 · outbound

This paper cites AMP robotics recycling reimagined.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting AMP robotics recycling reimagined

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:10.045705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f232e69b-9d11-4f2c-8b7d-1574d0e17497 · outbound

This paper cites Grey parrot waste intelligence.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting Grey parrot waste intelligence

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:09.895742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c9a2bb93-95c2-484e-acab-2200af086d0c · outbound

This paper cites TITECH plastic sorting technology.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting TITECH plastic sorting technology

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:09.762559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 970b87da-987e-4d8b-986e-74eb5bf6ed86 · outbound

This paper cites Rich feature hierarchies for accurate object detection and semantic segmentation,.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting Rich feature hierarchies for accurate object detection and semantic segmentation,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:09.592646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 010b0735-f14c-4837-b017-2da28acbc558 · outbound

This paper cites Fast r-cnn,.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting Fast r-cnn,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:09.517147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 27e29f11-7e8d-47a9-9975-969c69877e32 · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal net- works,.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting Faster r-cnn: Towards real-time object detection with region proposal net- works,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:09.352532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f625004b-a384-4e59-a2b5-74c495c5c02a · outbound

This paper cites Mask r-cnn,.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting Mask r-cnn,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:09.216425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5c5bb743-dd18-4223-b31e-230a6660ca89 · outbound

This paper cites Game theory of mind,.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting Game theory of mind,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:09.025786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8a90088b-9612-45b5-8925-0c3c3719330b · outbound

This paper cites Deep residual learning for image recognition,.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting Deep residual learning for image recognition,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T15:01:04.620576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c72299a6-c56d-4c00-adb9-de6c3d11675f · outbound

This paper cites Cspnet: A new backbone that can enhance learn- ing capability of CNN,.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting Cspnet: A new backbone that can enhance learn- ing capability of CNN,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:08.891861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 97a67543-2275-4374-b50e-1cc31cbe4e60 · outbound

This paper cites Efficientnet: Rethinking model scaling for convolutional neural networks,.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting Efficientnet: Rethinking model scaling for convolutional neural networks,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:08.729621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d4790839-2688-4cc1-b885-0bffcdecaefd · outbound

This paper cites You only look once: Unified, real-time object detection,.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting You only look once: Unified, real-time object detection,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T15:01:04.904200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 681ca0c3-3301-4649-ad5a-f39c45ee85e2 · outbound

This paper cites SSD: single shot multibox detector,.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting SSD: single shot multibox detector,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:08.625643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4e28f7af-133a-4711-a457-e819885e87a0 · outbound

This paper cites Focal loss for dense object detection,.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting Focal loss for dense object detection,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:08.466854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 53aa82d7-48d5-4dc4-ae77-0b9b539f4e82 · outbound

This paper cites UN environment programme on plastic pollution.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting UN environment programme on plastic pollution

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:08.334891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 37f9bbda-d614-47df-b3fd-85582828628f · outbound

This paper cites EPA plastics material specific data.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting EPA plastics material specific data

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:08.172178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1fe56424-6287-4ebe-8661-afae47592d25 · outbound

This paper cites National recycling strategy: Part one of a series on building a circular economy for all,.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting National recycling strategy: Part one of a series on building a circular economy for all,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:08.028329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4ddb5ae5-f91a-4cb4-9a57-43c557d192ac · outbound

This paper cites an unresolved cited work.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:01:07.959987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 29ab9105-b646-4bea-aebc-d0a008d77020 · outbound

This paper cites Procter & Gamble - HolyGrail.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting Procter & Gamble - HolyGrail

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:07.756890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3069456f-c0db-4703-855f-42d2eb050cb9 · outbound

This paper cites BASF - News Releases.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting BASF - News Releases

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:07.620499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d3b186a8-8ff9-4a7c-97a6-c2e446e728ee · outbound

This paper cites Classification of plastic bottles based on visual and physical features for waste management,.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting Classification of plastic bottles based on visual and physical features for waste management,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:07.373913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 664eb340-cb40-4f28-ac0a-6d4e4df65d7a · outbound

This paper cites Advancing plastic waste classification and recycling efficiency: Integrating image sensors and deep learning algorithms,.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting Advancing plastic waste classification and recycling efficiency: Integrating image sensors and deep learning algorithms,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:07.219353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1ff1cf40-3586-4842-b2c1-80e77a668944 · outbound

This paper cites Zerowaste dataset: Towards deformable object segmentation in cluttered scenes,.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting Zerowaste dataset: Towards deformable object segmentation in cluttered scenes,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:06.989601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 38f2eaf7-29c8-4e3d-b9af-aa48f0a73e8a · outbound

This paper cites One-Shot learning based classification for segregation of plastic waste.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting One-Shot learning based classification for segregation of plastic waste

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:01:06.366579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d8e54ba1-8257-46d7-843a-b566b57f3938 · outbound

This paper cites Cross-modal generative models for multi- modal plastic sorting,.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting Cross-modal generative models for multi- modal plastic sorting,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:06.780420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 721dd216-46a7-445f-9f24-dd9d082f19b2 · outbound

This paper cites Grad-cam: Visual explana- tions from deep networks via gradient-based localization,.

Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting Grad-cam: Visual explana- tions from deep networks via gradient-based localization,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:01:06.606493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.