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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.

source=pdf_text observed=2026-08-14T15:44:59.373771Z digest=sha256:e89016b6ec1f3e6e81e953b5c39467ab78f31e674e4b3cbb50cd32fcab2df2b4

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=sha256:0093abe99eb91c36f86d0e7173c82b33c37d9b46d7c058ab42e5aa1aa280f389

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
raw_fallback, observed 2026-08-14T15:44:59.647657Z

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:c9f5d608d7834ca9aa1e417f84eea4db5406077abe40ce96030e021ad4d49035

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=sha256:208824e0c655fc3f697d8024c9e46aea341c81da228d7ddf70393e60c492595e

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.

source=pdf_text observed=2026-08-14T15:44:59.391039Z digest=sha256:944cd4905e46f7a00850afb3ed41cbadf21d83195d8a4a246329a16b927f2865

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=sha256:99d6ea54d3e80bbee0c0f0b786dba07c6438d564d2be73b65eb2c2429c407d9a

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=sha256:751b89e640e4b5e401701a2c71b303e3ef17b9e926bce81c4be945e2b1d5bd4f

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:cfba0e0fb40846c73e75ac77b8c47d32653ce833f2149d7e60b757ad637fa6e0

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=sha256:24bce7dae544772acee5627bd5dfe96c58a8c78dccd92f34f952a481a86bb5c9

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:a32e8a92b7b4e25507d9803de9c90f395a5c2b4b1573b55c2719a168abd8852b

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:c880b0205e57201a566a4ca442f56f5312af17a3d55af7fc65b2c044f7292107

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=sha256:27763e7124c1bf63b66975556182a8497bcc3ac16998a20c6ff4a7d4fc6c90e7

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=sha256:87c6f6487a372bf0fbb6a72e54708e955d7ccea9f6bc49bd10e25b8cb9bd27c7

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:f871b3fa3f140b3f844fb252ee5e76c16b66261173850a5e0f4e3f15e08f0129

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=sha256:392b3e92d29479df9b6135d8efc66fa379dcee6c1592524f6111a67ae1b1215d

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=sha256:40a2406c9d5ce5000705cf39c5fdd044495431b065e88f539b83dda5302a40d4

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=sha256:532883971e4529f40402fe7ed5b8826d6d080b5e8e8dc1b334652fc63bfff43a

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=sha256:7a4b75ae6c6ec5cc577e6cea8d789e7f2dd15fb324c186a855fb4b924b0ffe8d

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:c4a798cf86d6c828c4c5d65b4d7973e555f0ce05143785bd83d9e6283c6c90e6

Pith citing papers

No inbound Pith citation observations are available.