Pith. sign in

Paper Citation Record · LEDGER

Assessing Knee OA Severity with CNN attention-based end-to-end architectures

As of 16 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:1908.08856.

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

pith.paper-citation-record.v1
1908.08856 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:30:20.724556Z

measured 33 of 33 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

33 of 33 outbound references displayed

  • verified exact0
  • verified fuzzy24
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0eb2d045-3c3f-4d1c-a40f-ef5573bdb0d4 · outbound

This paper cites Quantifying radiographic knee osteoarthritis severity using deep convolutional neural networks.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Quantifying radiographic knee osteoarthritis severity using deep convolutional neural networks

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:21.242245Z

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=arxiv_source observed=2026-08-14T11:30:20.564741Z digest=sha256:9015ee0c005b17d88f2d41c8d51b5dfa0cdbb19dd353ff1ce07ede311ca18da5

Observation 29ad3d7c-ba60-4df6-b1d3-4fb0abfc831d · outbound

This paper cites Automatic detection of knee joints and quantification of knee osteoarthritis severity using convolutional neural networks.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Automatic detection of knee joints and quantification of knee osteoarthritis severity using convolutional neural networks

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:21.228366Z

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=arxiv_source observed=2026-08-14T11:30:20.570477Z digest=sha256:683a976b4b5b0a733f67c9740b832973bef0baf8aaf95ab5cb4bdd32226b3ff8

Observation 74c06cf7-1531-40f3-b7fa-7295de441f7a · outbound

This paper cites Neural codes for image retrieval.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Neural codes for image retrieval

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:21.212778Z

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=arxiv_source observed=2026-08-14T11:30:20.575737Z digest=sha256:c735e66d0841ed422d339e1f1e3e3794b857275ea55c98e637286227945e4577

Observation 9eca5474-a1c2-4b9d-ac26-bbf0ad7d9f50 · outbound

This paper cites Return of the Devil in the Details: Delving Deep into Convolutional Nets.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Return of the Devil in the Details: Delving Deep into Convolutional Nets

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-14T11:30:20.581423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T11:30:20.581423Z digest=sha256:a8f58eff8378019ca5942a23d6db66097bfac6e03db004e65bf59d795d8197bc

Observation 75d28a8f-b3df-4dc5-84db-d3678c62f571 · outbound

This paper cites Locally-connected and convolutional neural networks for small footprint speaker recognition.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Locally-connected and convolutional neural networks for small footprint speaker recognition

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:21.197385Z

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=arxiv_source observed=2026-08-14T11:30:20.589590Z digest=sha256:9f7a66251853b384f179e52723613ed5dbbbd35b220d9a9b17502114115b3376

Observation 005796d2-3a18-4b7c-8d06-8eb9938869f0 · outbound

This paper cites A coefficient of agreement for nominal scales.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures A coefficient of agreement for nominal scales

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-14T11:30:20.596108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T11:30:20.596108Z digest=sha256:d389a89f509f035e70ccc4a85c7987d3a93a9974207bf00faee6d235c9d3a788

Observation dc05faf1-76c1-45e1-85c6-a3cbb0f947a5 · outbound

This paper cites A unified architecture for natural language processing: Deep neural networks with multitask learning.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures A unified architecture for natural language processing: Deep neural networks with multitask learning

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:21.170682Z

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=arxiv_source observed=2026-08-14T11:30:20.602394Z digest=sha256:4f9b8d39072ca2ade7bfb5f243e48d75c834833419a6a49218e3d4293a7ddad8

Observation 94bb22cd-ec9a-4002-bb63-6e4ff8d50725 · outbound

This paper cites Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:21.153376Z

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=arxiv_source observed=2026-08-14T11:30:20.607042Z digest=sha256:987502aa6f545b1ba6fdba93cc20b73476c22b842bbec6cb92e67258abb7dd17

Observation 5e87ba94-ac16-4e58-9e6b-62d317ed20df · outbound

This paper cites Deep residual learning for image recognition.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Deep residual learning for image recognition

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-14T11:30:20.611532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T11:30:20.611532Z digest=sha256:42208bcb23fb752c3216ff4180a888ba866ff226c2977b2c000d381c78e0723d

Observation ae74d5fc-ea36-4646-99ff-f295e08368ca · outbound

This paper cites Knee osteoarthritis prevalence, risk factors, pathogenesis and features: Part i.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Knee osteoarthritis prevalence, risk factors, pathogenesis and features: Part i

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:21.122005Z

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=arxiv_source observed=2026-08-14T11:30:20.618161Z digest=sha256:86a73896e7ee7966234f804a8922262f1dd71c302cfe2af3bcec09d1a415dfc0

Observation f30bd9c1-b1eb-4147-8038-67b9cd2dfd86 · outbound

This paper cites Cross-language knowledge transfer using multilingual deep neural network with shared hidden layers.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Cross-language knowledge transfer using multilingual deep neural network with shared hidden layers

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:21.105025Z

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=arxiv_source observed=2026-08-14T11:30:20.623562Z digest=sha256:b51cafced10493dd47e9707200af834b8ea61feffa6808ae4d1a76a810ad7668

Observation 73bed5d8-fa29-407c-b754-6dce51650f00 · outbound

This paper cites Learn To Pay Attention.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Learn To Pay Attention

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-14T11:30:20.629174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T11:30:20.629174Z digest=sha256:77541529db49f8df59fb2d988cbcdb2f6f59e86dced69eb3db64f0525d1a6b5b

Observation 211b92cd-8210-4719-82d4-e29f3eb2f8ee · outbound

This paper cites Caffe: Convolutional architecture for fast feature embedding.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Caffe: Convolutional architecture for fast feature embedding

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:21.084617Z

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=arxiv_source observed=2026-08-14T11:30:20.634881Z digest=sha256:fb2c4234a07399996e847c0a7d332a8bbd5225aaf763f658c93ee9c05e973423

Observation b68e7e54-7b49-40e4-ad9d-c2402ddebf9f · outbound

This paper cites Recognizing Image Style.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Recognizing Image Style

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-14T11:30:20.639130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T11:30:20.639130Z digest=sha256:d3781fb33aeb802acef5bf257f86b999544735a3b2274064367d65b707ed5cb1

Observation 95f4eab6-82ad-434d-a33e-e345fdb44fcc · outbound

This paper cites Radiological assessment of osteo-arthrosis.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Radiological assessment of osteo-arthrosis

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:21.068917Z

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=arxiv_source observed=2026-08-14T11:30:20.643597Z digest=sha256:f665a68b2ef12cc4de37b407f8d3dc66a4591039c1923e7742750cd3f4d45828

Observation 30fac028-1d88-4f10-88c4-a3912564571e · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Adam: A Method for Stochastic Optimization

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-14T11:30:20.650023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T11:30:20.650023Z digest=sha256:724b0fa0b56b5294ba1ebd3131d1f31b91fe25b38601aaced1d16cdccb4d1ee2

Observation 050ee9da-a85e-40e7-8799-88f758a92314 · outbound

This paper cites Reliability and accuracy of cross-sectional radiographic assessment of severe knee osteoarthritis: role of training and experience.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Reliability and accuracy of cross-sectional radiographic assessment of severe knee osteoarthritis: role of training and experience

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:21.053681Z

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=arxiv_source observed=2026-08-14T11:30:20.653862Z digest=sha256:bf7d0105a7b940452e0063f1293123294b993a9203c360ffaeb0eab52e06e10b

Observation 02abe8a4-55fc-4cde-881e-518ad4c2f02d · outbound

This paper cites Ubernet: Training a universal convolutional neural network for low-, mid-, and high-level vision using diverse datasets and limited memory.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Ubernet: Training a universal convolutional neural network for low-, mid-, and high-level vision using diverse datasets and limited memory

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:21.037523Z

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=arxiv_source observed=2026-08-14T11:30:20.657401Z digest=sha256:d57e9419c3379ae947d358fcf6fb3372d60f4e0f84df64cf9dd733beaa7112f9

Observation e2dd79f7-70d2-4e48-afce-8b32cb28a426 · outbound

This paper cites Imagenet classification with deep convolutional neural networks.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Imagenet classification with deep convolutional neural networks

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-14T11:30:20.661125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T11:30:20.661125Z digest=sha256:cfd328b9a448ebb5b6a92ff06c0c7a2c1f5357b21745e30c20b950b3bcf9fa26

Observation c6f833b8-32ac-47a4-9627-1c9839169678 · outbound

This paper cites Face recognition: A convolutional neural-network approach.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Face recognition: A convolutional neural-network approach

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:21.009071Z

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=arxiv_source observed=2026-08-14T11:30:20.664522Z digest=sha256:9a0c0f0e4df95f7d753e707355435d457952191ca207c005ac5afb619656ff91

Observation ccdd5493-9122-4020-984e-f67e05aef285 · outbound

This paper cites The age-related changes in cartilage and osteoarthritis.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures The age-related changes in cartilage and osteoarthritis

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:20.993550Z

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=arxiv_source observed=2026-08-14T11:30:20.668281Z digest=sha256:9e6a4c3f165ba9cb163bdad870f9dfd610ef8e6110f947bb1e76eae2314afda8

Observation 86cab7f9-4ca9-4bfe-b037-dd6af224a1a7 · outbound

This paper cites Fully Convolutional Attention Networks for Fine-Grained Recognition.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Fully Convolutional Attention Networks for Fine-Grained Recognition

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-14T11:30:20.672102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T11:30:20.672102Z digest=sha256:a4b5e76f98cbf69fee458de707f8be954be3ab386808afc7bb75d8215367f193

Observation 5cb8aa13-2783-449b-8636-c3b6b48da905 · outbound

This paper cites Attention on pretrained-vgg16 for bone age.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Attention on pretrained-vgg16 for bone age

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:20.976876Z

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=arxiv_source observed=2026-08-14T11:30:20.677987Z digest=sha256:b4270d3e4fe357eaa6b2c0d1c2732fc4f564b3e9092f823a430d8ae2619db088

Observation 87784d40-8349-47ac-ae47-35cced3d12fc · outbound

This paper cites Fully automatic quantification of knee osteoarthritis severity on plain radiographs.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Fully automatic quantification of knee osteoarthritis severity on plain radiographs

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:20.960866Z

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=arxiv_source observed=2026-08-14T11:30:20.682596Z digest=sha256:4fcfe58eec12e1943b67a6cf577e07dc3099a7b1bda7fb7d3fa1b8df7a6d9191

Observation bcfe45b7-69e8-401a-a9a2-bfed1e8d84a0 · outbound

This paper cites Imagenet large scale visual recognition challenge.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Imagenet large scale visual recognition challenge

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:20.948314Z

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=arxiv_source observed=2026-08-14T11:30:20.687189Z digest=sha256:436c79c213fd1916e925a8b5e29bc9414ecaf51ec01dffbeaf3acd97c3f081ae

Observation ba3cb13c-d405-4988-a89d-db8fe2764dd2 · outbound

This paper cites Wndchrm--an open source utility for biological image analysis.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Wndchrm--an open source utility for biological image analysis

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:20.935803Z

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=arxiv_source observed=2026-08-14T11:30:20.691868Z digest=sha256:25eda538dd98607f61ed60e4e35a4d7ee468bfa8a4c8f57d7edd6ee82f3fc448

Observation bc66cb39-7e6d-43fc-bc29-5e6c82012e96 · outbound

This paper cites Early detection of radiographic knee osteoarthritis using computer-aided analysis.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Early detection of radiographic knee osteoarthritis using computer-aided analysis

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:20.920252Z

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=arxiv_source observed=2026-08-14T11:30:20.696126Z digest=sha256:816f3327e0ebd7f84f0e8ac9f561d8a088c44e351554e27d44e9e6e50754a329

Observation 3770a3db-690a-4af3-8fec-90324e3d6ff2 · outbound

This paper cites Knee x-ray image analysis method for automated detection of osteoarthritis.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Knee x-ray image analysis method for automated detection of osteoarthritis

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:20.904815Z

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=arxiv_source observed=2026-08-14T11:30:20.700883Z digest=sha256:1bd394d6e54b8fbadd5e2c99508d58561ff07500d44dcfcbe11c33e5d02ca78a

Observation 76db8fd6-c555-458c-b8e3-47c37b327d35 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-14T11:30:20.706662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T11:30:20.706662Z digest=sha256:87d897241b981ed9ea69c3cb55d5bf50c26788f14761d44d3b91143c72b24c4d

Observation 252e33e1-5ebc-4bfc-a7ac-63a05bb4d34a · outbound

This paper cites Automatic knee osteoarthritis diagnosis from plain radiographs: a deep learning-based approach.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Automatic knee osteoarthritis diagnosis from plain radiographs: a deep learning-based approach

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:20.888833Z

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=arxiv_source observed=2026-08-14T11:30:20.710988Z digest=sha256:9796c55e7f03894365616fff6b2b38a34a008e8db6e5d07aff09226ef27ec068

Observation abecbe10-18e4-4c49-9621-3c3b83c1907d · outbound

This paper cites Computer-aided detection of breast masses: Four-view strategy for screening mammography.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Computer-aided detection of breast masses: Four-view strategy for screening mammography

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:20.873332Z

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=arxiv_source observed=2026-08-14T11:30:20.715305Z digest=sha256:0a33cfb1c785f184265574a38c8eb9b03c83b086d631b0a905aefb9b26abd6f0

Observation 0fa820c7-4da8-4300-9851-80b04cc98c61 · outbound

This paper cites The application of two-level attention models in deep convolutional neural network for fine-grained image classification.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures The application of two-level attention models in deep convolutional neural network for fine-grained image classification

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:20.856585Z

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=arxiv_source observed=2026-08-14T11:30:20.719504Z digest=sha256:e58246846d50df980d60be87da77db88e5958c8de6f66348ff2cfef3df549dfe

Observation 44605ea5-a822-46ca-af48-47fd3feb48a2 · outbound

This paper cites Simple scoring system and artificial neural network for knee osteoarthritis risk prediction: a cross-sectional study.

Assessing Knee OA Severity with CNN attention-based end-to-end architectures Simple scoring system and artificial neural network for knee osteoarthritis risk prediction: a cross-sectional study

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:30:20.840909Z

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=arxiv_source observed=2026-08-14T11:30:20.724556Z digest=sha256:b30afe55b82efa194b048f3fffd5e51b23b9de11afdf0d46762fa1c69dc70c4a

Pith citing papers

No inbound Pith citation observations are available.