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Paper Citation Record · LEDGER

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features

As of 16 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:1908.00669.

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

pith.paper-citation-record.v1
1908.00669 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T15:44:59.437736Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

20 of 20 outbound references displayed

  • verified exact1
  • verified fuzzy14
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d889c81a-3287-4fda-90bf-399aeaf1370a · outbound

This paper cites Ilsvrc-2012,.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features Ilsvrc-2012,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:44:59.684445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 82089856-032f-461f-8912-73c50997d56c · outbound

This paper cites Microsoft coco: Common objects in context.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features Microsoft coco: Common objects in context

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-14T15:44:59.373771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 309f991e-cdf1-490e-bb1c-521a200bcb74 · outbound

This paper cites Fully convolutional networks for semantic segmentation.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features Fully convolutional networks for semantic segmentation

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-14T15:44:59.378270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T15:44:59.378270Z digest=sha256:e007e57246ef8384318af35327d73e14389fb116a79b5ba5426586eca5bc760d

Observation 5631b1d6-18d1-4d01-bae8-7f0ecb34c590 · outbound

This paper cites Understanding convolution for semantic segmentation.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features Understanding convolution for semantic segmentation

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T15:44:59.382873Z digest=sha256:6ebfb8f1184987bbd8087bfe17e264738dce890ac925dd6260310a94f0dd57a1

Observation c6d41cff-b871-43c2-a28f-5ad82dfd7bf0 · outbound

This paper cites an unresolved cited work.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-14T15:44:59.636538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T15:44:59.386834Z digest=sha256:b5e3100903aef4dcfe225e8873c1b63dc5b0c65441baa190e0a4162b918f073a

Observation ae3a04a1-6a3b-42e7-98a7-4c197d46fd90 · outbound

This paper cites Deep learning advances in computer vision with 3d data: A survey.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features Deep learning advances in computer vision with 3d data: A survey

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:44:59.624042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 8bc6651b-c912-40c1-a099-35296f25078b · outbound

This paper cites Deformable convnets v2: More deformable, better results.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features Deformable convnets v2: More deformable, better results

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:44:59.612219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T15:44:59.394518Z digest=sha256:28230a0366d6fe75754ea6118566817c09569df6730448ae7f7f9b7523c07f20

Observation ae17204c-ac9e-46af-9139-bace268062d0 · outbound

This paper cites Efficient semantic image segmentation with superpixel pooling.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features Efficient semantic image segmentation with superpixel pooling

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-14T15:44:59.398113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T15:44:59.398113Z digest=sha256:28c41c9068b56a35ff1855675a3873f22e20ab3f0a8eb18d6cce6197f98938a2

Observation 2e1a30aa-abff-4e15-8dd2-4f98b9512722 · outbound

This paper cites Achanta, A.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features Achanta, A

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:44:59.600692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T15:44:59.402427Z digest=sha256:96aec01ea614a9411405960c67861c91779cf10136e00f79e75f1122803a5b0b

Observation 295b3901-c2a6-42c9-b77e-a2f91b2d6751 · outbound

This paper cites Fast cloud image segmentation with superpixel analysis based convolutional networks.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features Fast cloud image segmentation with superpixel analysis based convolutional networks

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:44:59.589630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T15:44:59.405825Z digest=sha256:3ad25f7ea73b5400669f129bdd88dfe411518e9d4c29412e749c6f964d2d7172

Observation 04ccd995-4c7f-44ee-aaaf-c97ddeb986cf · outbound

This paper cites Feedforward semantic segmentation with zoom-out features.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features Feedforward semantic segmentation with zoom-out features

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:44:59.578748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T15:44:59.409354Z digest=sha256:2529ee72af81f96d4160f3deaa4f42406d64afea640c36b20032550214af734c

Observation bce5e9b0-e288-4ed4-977d-8d9b361e24a0 · outbound

This paper cites Dynamic routing between capsules.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features Dynamic routing between capsules

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:44:59.567628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T15:44:59.412971Z digest=sha256:f1b018bf8245285591d9a3b3ec3b0191d937edccb02b0c6da9bc610af7903c48

Observation 3a5c73dd-d58a-4047-902c-4d61904378de · outbound

This paper cites U-net: Convo- lutional networks for biomedical image segmentation.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features U-net: Convo- lutional networks for biomedical image segmentation

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:44:59.555881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T15:44:59.416428Z digest=sha256:8e009f6d016935d094c2d1a3b3c3633903f0c306ae70d5d64b97e51fae598921

Observation 637ae177-f20b-4c52-847d-aadce3067635 · outbound

This paper cites Capsdemm: Capsule network for detection of munros microabscess in skin biopsy images.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features Capsdemm: Capsule network for detection of munros microabscess in skin biopsy images

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:44:59.544030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T15:44:59.420118Z digest=sha256:65a08f66dab93f9d67222a84509e5f5d1d9bb2305a50d46f87add2794b9dacd0

Observation 1ea86f81-e6f3-4781-b925-0d87d2d8a7b8 · outbound

This paper cites Capsules for Object Segmentation.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features Capsules for Object Segmentation

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-14T15:44:59.423182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T15:44:59.423182Z digest=sha256:112d389b6cf5efcdd94839d899fb789ba17fea0fe846c8cf3c27688c3199b62f

Observation 25f266bd-cca0-4f1b-a1fa-9acb29d24ae1 · outbound

This paper cites gSLICr: SLIC superpixels at over 250Hz.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features gSLICr: SLIC superpixels at over 250Hz

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-08-14T15:44:59.475374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T15:44:59.426919Z digest=sha256:c4e5055258cf175076e7228a738000fa8b52ebd5b94a829747b2b5aa79d7ed4c

Observation 6b2a2d88-22ea-4dd1-8e4a-925e3162b29b · outbound

This paper cites Matrix capsules with em routing.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features Matrix capsules with em routing

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:44:59.531995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T15:44:59.430978Z digest=sha256:8f2d3e65cd81fcd2ca7074a89cfdbed6f7e636bf759b597d047131b995be40c1

Observation a53f72f0-0d84-48fc-8e02-ceaaefe11eae · outbound

This paper cites Simonyan and A.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features Simonyan and A

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:44:59.519918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T15:44:59.434223Z digest=sha256:43229a4fbd5e07bad2e36a449af69dca70f0707dbbec83614545bfa3dcbef41a

Observation 98470663-97fc-40f2-a5d3-8ca6b2f25182 · outbound

This paper cites Linnaeus 5 dataset for machine learning.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features Linnaeus 5 dataset for machine learning

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:44:59.508389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T15:44:59.437736Z digest=sha256:b62a36a4ccacebd18f50723007fef2d317529dedebd851b8af0cdbc156f66edd

Observation a491d0c2-33d3-4c03-8a8a-73256127b365 · outbound

This paper cites image-net.

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features image-net

Reference 2012

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:44:59.672822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T15:44:59.369628Z digest=sha256:d2f846e6ffd05a703bb617c0fc880737212ddb90f4cbcd5fc3f41c1760602c91

Pith citing papers

No inbound Pith citation observations are available.