Paper Citation Record · LEDGER

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce

As of 12 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2411.16219.

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

pith.paper-citation-record.v1
2411.16219 v2

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:29:52.898148Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

33 of 33 outbound references displayed

verified exact0
verified fuzzy27
unresolved6
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 564c5863-9eb8-490e-8680-1c878432288c · outbound

This paper cites Automated sorting and grading of agricultural products based on image processing.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Automated sorting and grading of agricultural products based on image processing

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.298821Z

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Observation 69ca72d4-77d4-490f-a776-2d7e322b55cc · outbound

This paper cites A Cookbook of Self-Supervised Learning.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce A Cookbook of Self-Supervised Learning

Reference 2

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Observation c28f1c1f-073e-47d3-bbe0-941b2f99c183 · outbound

This paper cites New trends in the de- velopment and application of artificial intelligence in food processing.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce New trends in the de- velopment and application of artificial intelligence in food processing

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.290052Z

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Observation be56aef6-4776-44ab-9307-2667f926be0a · outbound

This paper cites Schwing, and Alexander Kirillov.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Schwing, and Alexander Kirillov

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.280865Z

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Observation a437d1e0-444f-4628-b21a-81c8ae6ce626 · outbound

This paper cites Schwing, Alexander Kirillov, and Rohit Girdhar.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Schwing, Alexander Kirillov, and Rohit Girdhar

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.272275Z

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Observation 3d95987a-c56b-4b00-87a9-1895e330af52 · outbound

This paper cites Neill, and Artur Dubrawski.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Neill, and Artur Dubrawski

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.264326Z

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Observation e73ce7d6-7b91-4a5b-9284-91d8d4555add · outbound

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

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.256149Z

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Observation 9134013d-d19d-4692-ac56-6109579b4bea · outbound

This paper cites Everingham, L.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Everingham, L

Reference 8

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Observation c3688b36-f46e-4771-9132-1c1992b69605 · outbound

This paper cites Girshick.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Girshick

Reference 9

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Source-reported events for the cited work

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Observation abd181ad-5d1d-4d3b-a38b-3760180e6466 · outbound

This paper cites What makes for effective detection pro- posals? IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(4):814–830, 2015.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce What makes for effective detection pro- posals? IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(4):814–830, 2015

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.228912Z

Source-reported events for the cited work

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Observation 44b11448-92d4-4aef-9348-34eb7802673f · outbound

This paper cites A foundation model for cell segmentation.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce A foundation model for cell segmentation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.220340Z

Source-reported events for the cited work

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Observation 7aadd683-78fe-4f01-8dec-f47a27eb1ff9 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Adam: A Method for Stochastic Optimization

Reference 12

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Observation 23fc1f36-7cf0-4119-8d7e-93cee484d20f · outbound

This paper cites Girshick, Kaiming He, and Piotr Dollár.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Girshick, Kaiming He, and Piotr Dollár

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.210899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 400a4ffb-4ffd-45be-b786-5db58e8c2e8d · outbound

This paper cites Panoptic segmen- tation.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Panoptic segmen- tation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.202451Z

Source-reported events for the cited work

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Observation c8f767b4-0a03-43b6-a32c-cd68564b16df · outbound

This paper cites Segment Anything.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Segment Anything

Reference 15

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Source-reported events for the cited work

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Observation fe671f5c-b39d-4f28-ad85-7c68bc757b2e · outbound

This paper cites Facilitated machine learning for image-based fruit quality assessment.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Facilitated machine learning for image-based fruit quality assessment

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.193632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 773cfd4f-5486-4f48-94a5-75dd41ed0cbd · outbound

This paper cites Multimodal foundation models: From special- ists to general-purpose assistants.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Multimodal foundation models: From special- ists to general-purpose assistants

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.184347Z

Source-reported events for the cited work

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Observation 1b04d5c1-e2f5-4a9d-9509-881565800a35 · outbound

This paper cites Microsoft coco: Com- mon objects in context.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Microsoft coco: Com- mon objects in context

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.175734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 836fa2af-fae6-4b6e-a7b3-5dd5809adb20 · outbound

This paper cites A visual-language foundation model for com- putational pathology.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce A visual-language foundation model for com- putational pathology

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.167420Z

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Observation b71419f2-fa02-4f2e-9353-afaea5f032c1 · outbound

This paper cites Open Source Computer Vision Library,.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Open Source Computer Vision Library,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.158716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8d8ebd6c-2d54-4535-8dfc-fdcd4d1eb684 · outbound

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

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce SAM 2: Segment Anything in Images and Videos

Reference 21

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Observation 512355e4-0ad1-460b-8384-18afa2e5f6f9 · outbound

This paper cites ViNT: A Foundation Model for Visual Navigation.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce ViNT: A Foundation Model for Visual Navigation

Reference 22

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Source-reported events for the cited work

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Observation 894fb1c9-4661-406f-95b1-b29f0564c31f · outbound

This paper cites Get another label? improving data qual- ity and data mining using multiple, noisy labelers.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Get another label? improving data qual- ity and data mining using multiple, noisy labelers

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.150074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0c17d81a-db0f-478a-b1d0-bc4fb6320e2f · outbound

This paper cites Label Studio: Data labeling software, 2020.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Label Studio: Data labeling software, 2020

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.141092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9cb5fb16-1327-47db-a300-aff9aa8e8814 · outbound

This paper cites The multidimensional wisdom of crowds.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce The multidimensional wisdom of crowds

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.131218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0178a9a2-b2d4-4686-a785-50b99d9942df · outbound

This paper cites SegFormer: Simple and efficient design for semantic segmentation with transformers.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce SegFormer: Simple and efficient design for semantic segmentation with transformers

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.122139Z

Source-reported events for the cited work

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Observation c4d4a0a0-ae18-433d-9909-8df06d36a99f · outbound

This paper cites Depth any- thing: Unleashing the power of large-scale unlabeled data.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Depth any- thing: Unleashing the power of large-scale unlabeled data

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.112217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8ff86b1b-4374-4435-8f5f-77127032559e · outbound

This paper cites Implementation of information and communication technologies in fruit and vegetable supply chain: a systematic literature re- view.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Implementation of information and communication technologies in fruit and vegetable supply chain: a systematic literature re- view

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.102391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 35aa1aad-dc45-4f51-91fe-9eae309f58c7 · outbound

This paper cites Text2seg: Re- mote sensing image semantic segmentation via text- guided visual foundation models.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Text2seg: Re- mote sensing image semantic segmentation via text- guided visual foundation models

Reference 29

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Source-reported events for the cited work

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Observation 1c27c316-6f81-4da3-91f2-50a2e9156dbb · outbound

This paper cites Scene Pars- ing through ADE20K Dataset.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce Scene Pars- ing through ADE20K Dataset

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.092392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8903ae68-4e68-4308-a462-5509646242b0 · outbound

This paper cites old” and.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce old” and

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.082318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0b833f9e-bbe7-4b65-80ba-901defc55008 · outbound

This paper cites While this is generally considered high for machine learning tasks, defects can be small and, thus, only be represented by a few pixels, making them harder to categorize.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce While this is generally considered high for machine learning tasks, defects can be small and, thus, only be represented by a few pixels, making them harder to categorize

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.072337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b07d36bc-ad01-4dd1-99fe-7680663d1190 · outbound

This paper cites A more balanced distribution of categories and a larger number of defect samples are likely to improve categorization accuracy.

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce A more balanced distribution of categories and a larger number of defect samples are likely to improve categorization accuracy

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:29:53.062160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

No inbound Pith citation observations are available.