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Paper Citation Record · LEDGER

Emotion estimation from video footage with LSTM

As of 19 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2501.13432.

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

pith.paper-citation-record.v1
2501.13432 v3

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T16:11:55.527385Z

measured 34 of 34 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

34 of 34 outbound references displayed

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  • verified fuzzy21
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 77282fcd-5ea1-48c6-a3a6-37ac3b5a711f · outbound

This paper cites an unresolved cited work.

Emotion estimation from video footage with LSTM Unresolved cited work

Reference 1

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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.

source=pdf_text observed=2026-08-10T16:11:55.412671Z digest=sha256:5fc6fab4111ea77fcc49613cdbc230b5a45810ede832d9224ad9167beb856f2e

Observation 4e41b8a2-5ef8-4b74-8819-d33998984888 · outbound

This paper cites Challenges in representation learning: A report on three machine learning contests.

Emotion estimation from video footage with LSTM Challenges in representation learning: A report on three machine learning contests

Reference 2

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raw_fallback, observed 2026-08-10T16:11:55.881891Z

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

source=pdf_text observed=2026-08-10T16:11:55.416935Z digest=sha256:d751426ec3836f38a1bcd84ac675b6f58bc4f2c4602297573488b9b675e53c34

Observation 418abca0-d45c-4269-a95f-318a91483333 · outbound

This paper cites Mediapipe: A framework for perceiving and processing reality.

Emotion estimation from video footage with LSTM Mediapipe: A framework for perceiving and processing reality

Reference 3

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raw_fallback, observed 2026-08-10T16:11:55.871440Z

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.

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Observation 37ef413d-8596-45ab-91a9-d66ee2420be0 · outbound

This paper cites Facial emotion recognition using handcrafted features and cnn.Procedia Computer Science, 218:1295–1303, 2023.

Emotion estimation from video footage with LSTM Facial emotion recognition using handcrafted features and cnn.Procedia Computer Science, 218:1295–1303, 2023

Reference 4

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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.

source=pdf_text observed=2026-08-10T16:11:55.424055Z digest=sha256:fc75b671a9aeba1784160627999aba8c4475fea035882a76ca29cdfca024cf21

Observation d67ef0db-6b27-4828-9520-66e49287627b · outbound

This paper cites A real-time robust facial expression recognition system using hog features.

Emotion estimation from video footage with LSTM A real-time robust facial expression recognition system using hog features

Reference 5

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raw_fallback, observed 2026-08-10T16:11:55.849912Z

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.

source=pdf_text observed=2026-08-10T16:11:55.427841Z digest=sha256:eba524a31cc252e48bca703ed07fdca3cddfb58275f2047e41d831079a15f25c

Observation 5a01f592-c58c-490a-9593-455f0aabd9fa · outbound

This paper cites Deep facial expression recognition: A survey.

Emotion estimation from video footage with LSTM Deep facial expression recognition: A survey

Reference 6

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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.

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Observation 0cdba29d-0a5f-4e90-82be-a95e6ca16ae0 · outbound

This paper cites Facial expression and body gesture emotion recognition: A systematic review on the use of visual data in affective computing.

Emotion estimation from video footage with LSTM Facial expression and body gesture emotion recognition: A systematic review on the use of visual data in affective computing

Reference 7

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raw_fallback, observed 2026-08-10T16:11:55.831230Z

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.

source=pdf_text observed=2026-08-10T16:11:55.434966Z digest=sha256:ec5dc37711d990fd306a4735482a261d842ce52a8a4d85b81a2cf452c9d60740

Observation e5f2960b-9a69-4741-822c-9b46f6147b9e · outbound

This paper cites Image processing with neural networks—a review.

Emotion estimation from video footage with LSTM Image processing with neural networks—a review

Reference 8

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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.

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Observation 1987dfd8-2f5c-4614-99e9-394ef0dd917f · outbound

This paper cites Development of real-time landmark-based emotion recognition cnn for masked faces.

Emotion estimation from video footage with LSTM Development of real-time landmark-based emotion recognition cnn for masked faces

Reference 9

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raw_fallback, observed 2026-08-10T16:11:55.812209Z

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.

source=pdf_text observed=2026-08-10T16:11:55.441334Z digest=sha256:464819d3754b191918e67b38463aef34a943e8ec7fd26b98ec9e46fcde0e80d8

Observation ce6f4110-966a-4483-80ef-c819060db657 · outbound

This paper cites MediaPipe: A Framework for Building Perception Pipelines.

Emotion estimation from video footage with LSTM MediaPipe: A Framework for Building Perception Pipelines

Reference 10

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-10T16:11:55.444793Z digest=sha256:2aead93e87cd58f75a9540c171810588ccd832075eec89dd9d168a0e791b32be

Observation 6140115e-eb34-425b-851f-1d080a5688c1 · outbound

This paper cites Emotion recognition at a distance: The robustness of machine learning based on hand-crafted facial features vs deep learning models.

Emotion estimation from video footage with LSTM Emotion recognition at a distance: The robustness of machine learning based on hand-crafted facial features vs deep learning models

Reference 11

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raw_fallback, observed 2026-08-10T16:11:55.801243Z

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

source=pdf_text observed=2026-08-10T16:11:55.448537Z digest=sha256:dc55ce702a66fa38822eab3f277ed085ec080426da3bfaccc5d27de627d3012d

Observation d298fd5a-625f-4fe2-bb82-3c5edf7acdde · outbound

This paper cites Comparison of facial landmark detection methods for micro-expressions analysis.

Emotion estimation from video footage with LSTM Comparison of facial landmark detection methods for micro-expressions analysis

Reference 12

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raw_fallback, observed 2026-08-10T16:11:55.788938Z

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.

source=pdf_text observed=2026-08-10T16:11:55.452534Z digest=sha256:953a72ddec848571794c1e6f64900c64b01ce532b313432d6091e79ebfc7d64c

Observation 66d8f029-7ce4-4fd7-a654-948d41daf9d1 · outbound

This paper cites Openface: An open source facial behavior analysis toolkit.

Emotion estimation from video footage with LSTM Openface: An open source facial behavior analysis toolkit

Reference 13

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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.

source=pdf_text observed=2026-08-10T16:11:55.456028Z digest=sha256:7ebf31922dff1d2f9c8a1d7ddb45f14a3c9d4a359d793288b8b47d3b05a6626c

Observation 251f69f4-e945-4d2c-88f6-f406e47e603e · outbound

This paper cites Murray, Benoit Steiner, Paul Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng.

Emotion estimation from video footage with LSTM Murray, Benoit Steiner, Paul Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng

Reference 14

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source=pdf_text observed=2026-08-10T16:11:55.459333Z digest=sha256:7603df3db2c078085ffccb861bc3917b2db7496c4ebb7f899b81f754a51aad95

Observation 5887de22-0c3a-49af-a451-66a94ca3e8ae · outbound

This paper cites Practice and theory of blendshape facial models.

Emotion estimation from video footage with LSTM Practice and theory of blendshape facial models

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-10T16:11:55.759713Z

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.

source=pdf_text observed=2026-08-10T16:11:55.463240Z digest=sha256:38e1c1cdcc911b04b5a1feacc0a8cb81162847f73bfdd1f3bbe7ac931c769ad9

Observation 66e4365f-5d4c-47e1-b1a7-0840e2d5279d · outbound

This paper cites What the face reveals: Basic and applied studies of spontaneous expression using the Facial Action Coding System (F ACS).

Emotion estimation from video footage with LSTM What the face reveals: Basic and applied studies of spontaneous expression using the Facial Action Coding System (F ACS)

Reference 16

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raw_fallback, observed 2026-08-10T16:11:55.749344Z

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.

source=pdf_text observed=2026-08-10T16:11:55.467222Z digest=sha256:2ca678bf77310c1ce5ca5affc20d2226b04f7e500fc5e31aae595aa5094cf4ba

Observation 12c8792d-d9ef-4656-b054-98924646a7c6 · outbound

This paper cites Facial expression and emotion.

Emotion estimation from video footage with LSTM Facial expression and emotion

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 34beaf5e-3b15-4a47-8ad3-6b478184e61e · outbound

This paper cites Presentation and validation of the radboud faces database.

Emotion estimation from video footage with LSTM Presentation and validation of the radboud faces database

Reference 18

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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.

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Observation a8ddba5f-b088-4f47-9c23-d0ea76acb331 · outbound

This paper cites Long short-term memory.

Emotion estimation from video footage with LSTM Long short-term memory

Reference 19

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raw_fallback, observed 2026-08-10T16:11:55.720261Z

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.

source=pdf_text observed=2026-08-10T16:11:55.477174Z digest=sha256:4060b2c70b31bd4feb9fddbbefe8895c462ee3174e3949f055bbf3ff004a7b25

Observation f82ab9c5-f76c-4b31-bb7c-47aa02eb34cf · outbound

This paper cites Deep learning, 2016.

Emotion estimation from video footage with LSTM Deep learning, 2016

Reference 20

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:11:55.480688Z digest=sha256:c9a7c9be1382b3163f72197da309d846b73cb1ee519ae13b74219ff02c961e6b

Observation 6f764be2-943a-4dc0-82b9-c8fcc556a1d4 · outbound

This paper cites Hybrid deep neural networks for face emotion recognition.

Emotion estimation from video footage with LSTM Hybrid deep neural networks for face emotion recognition

Reference 21

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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.

source=pdf_text observed=2026-08-10T16:11:55.483938Z digest=sha256:e17e45f0cd429be28382a96b0b23deb4f834625824d5e510918da89317f905d8

Observation 8ac84fb1-e74d-4113-8d93-da0b2aa845fe · outbound

This paper cites Web-based database for facial expression analysis.

Emotion estimation from video footage with LSTM Web-based database for facial expression analysis

Reference 22

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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.

source=pdf_text observed=2026-08-10T16:11:55.487034Z digest=sha256:bd2edfb3744997015c4f684e2d8fecade97b737aef62280cc072b64c7d36aec9

Observation 58981d33-61a0-4eff-99a5-59ec8c547bf0 · outbound

This paper cites Induced disgust, happiness and surprise: an addition to the mmi facial expression database.

Emotion estimation from video footage with LSTM Induced disgust, happiness and surprise: an addition to the mmi facial expression database

Reference 23

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raw_fallback, observed 2026-08-10T16:11:55.681375Z

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.

source=pdf_text observed=2026-08-10T16:11:55.490172Z digest=sha256:f6d78278d16ea1c8034480a6dec91a55d4516bd499d6b4cc60139d16e09e4e43

Observation 1bbed557-9a19-40d1-8bda-a103c1cf90bb · outbound

This paper cites From individual to group-level emotion recognition: Emotiw 5.0.

Emotion estimation from video footage with LSTM From individual to group-level emotion recognition: Emotiw 5.0

Reference 24

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raw_fallback, observed 2026-08-10T16:11:55.671452Z

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.

source=pdf_text observed=2026-08-10T16:11:55.493352Z digest=sha256:2afa72c5c8f9e902e728e79aa30c4a0adae0949d117aa0dc8b5d91c1a4dd8f74

Observation 3519a29c-1bf9-4cdf-ab95-bd07e4503c28 · outbound

This paper cites Multi-pie.

Emotion estimation from video footage with LSTM Multi-pie

Reference 25

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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.

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Observation 350f8fe2-cf63-46e3-aa03-1317e7872600 · outbound

This paper cites Affectnet: A database for facial expression, valence, and arousal computing in the wild.

Emotion estimation from video footage with LSTM Affectnet: A database for facial expression, valence, and arousal computing in the wild

Reference 26

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Observation 294b10ab-665a-44b3-9f7f-a9bd479d0677 · outbound

This paper cites Survey of resampling techniques for improving classification performance in unbalanced datasets.

Emotion estimation from video footage with LSTM Survey of resampling techniques for improving classification performance in unbalanced datasets

Reference 27

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Observation c5c56119-1878-4b08-9f20-84ee1594cf60 · outbound

This paper cites Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

Emotion estimation from video footage with LSTM Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Reference 28

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source=pdf_text observed=2026-08-10T16:11:55.505979Z digest=sha256:c4f7313e434eb26cf1b95eb621ca2c96859fff4d68347da81b24cc9cb10a5d42

Observation a258dd6d-0f17-46f2-a7e2-04e9816eaae1 · outbound

This paper cites Recurrent neural networks.

Emotion estimation from video footage with LSTM Recurrent neural networks

Reference 29

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Observation 60aab4e2-83c2-429f-acfb-3c8981dcb6cd · outbound

This paper cites Kerastuner.

Emotion estimation from video footage with LSTM Kerastuner

Reference 30

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:11:55.513013Z digest=sha256:5cbd81c4a31848d3167833d1ad63e742c6ce5159ae13db3bd97a64f281e2ccbe

Observation 370475d6-e56b-4e31-9d32-f64117767279 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Emotion estimation from video footage with LSTM Adam: A Method for Stochastic Optimization

Reference 31

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:11:55.516328Z digest=sha256:31f3671428398aa43ddeb10f90d79d88727693bf73c7dcd93880c49cb810f851

Observation 18f3d063-03f6-4927-be9f-1a2ce3d6bd6a · outbound

This paper cites Decoupled Weight Decay Regularization.

Emotion estimation from video footage with LSTM Decoupled Weight Decay Regularization

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:11:55.520288Z digest=sha256:23060fcb1e5302f74bb3bc4da7dd24d7631845166b970759f61e09764f169025

Observation f7108a62-abe0-4af2-a6fc-1dfa9774527e · outbound

This paper cites Springer New York, New York, NY , 2008.

Emotion estimation from video footage with LSTM Springer New York, New York, NY , 2008

Reference 33

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raw_fallback, observed 2026-08-10T16:11:55.625726Z

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.

source=pdf_text observed=2026-08-10T16:11:55.523990Z digest=sha256:3f18c41d19a195d9b65bf4b83c2eefc65eef363491acbc1ccad50c3bb8dc10dd

Observation 7da8d5c2-3e20-4641-808b-037dfdad34c1 · outbound

This paper cites Focal Loss for Dense Object Detection.

Emotion estimation from video footage with LSTM Focal Loss for Dense Object Detection

Reference 34

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