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Paper Citation Record · LEDGER

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels

As of 21 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2501.07750.

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

pith.paper-citation-record.v1
2501.07750 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:39:56.720766Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

27 of 27 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3205a052-81c9-4750-bb0b-f7df75cd555e · outbound

This paper cites Federated Distillation for Medical Image Classification: Towards Trustworthy Computer-Aided Diagnosis.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Federated Distillation for Medical Image Classification: Towards Trustworthy Computer-Aided Diagnosis

Reference 1

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Observation c900f673-d41d-40dc-8345-b7d5553d8abe · outbound

This paper cites Deep multi-class eye segmentation for ocular biometrics.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Deep multi-class eye segmentation for ocular biometrics

Reference 5

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Observation e34e8710-dc29-496c-a688-13474ab72945 · outbound

This paper cites PupilNet: Convolutional Neural Networks for Robust Pupil Detection.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels PupilNet: Convolutional Neural Networks for Robust Pupil Detection

Reference 7

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Observation 4f44cfd3-d090-4181-a193-dd96a6659a54 · outbound

This paper cites Less is more: Ensemble Learning for Retinal Disease Recognition Under Limited Resources.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Less is more: Ensemble Learning for Retinal Disease Recognition Under Limited Resources

Reference 11

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verified exact
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Observation 77613440-f401-4412-8b18-20efd3104ad2 · outbound

This paper cites Quality fusion based multimodal eye recognition.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Quality fusion based multimodal eye recognition

Reference 17

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Observation 66d11497-41d5-42ea-be8e-b2bcc354ef90 · outbound

This paper cites Sclera recog- nition using dense-sift.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Sclera recog- nition using dense-sift

Reference 18

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Source-reported events for the cited work

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Observation 5d866a39-5ddc-4616-ac0e-c28fda674133 · outbound

This paper cites A new efficient and adaptive sclera recognition system.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels A new efficient and adaptive sclera recognition system

Reference 19

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Source-reported events for the cited work

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Observation 4bfcc724-2e07-48ad-83e9-6d2e520c8ac9 · outbound

This paper cites Enhanced segmen- tation and complex-sclera features for human recognition with unconstrained visible-wavelength imaging.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Enhanced segmen- tation and complex-sclera features for human recognition with unconstrained visible-wavelength imaging

Reference 21

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Source-reported events for the cited work

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Observation dc02c7a5-2ed2-4ddf-88d0-8a0de28a77f4 · outbound

This paper cites Interpretable CNN-Multilevel Attention Transformer for Rapid Recognition of Pneumonia from Chest X-Ray Images.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Interpretable CNN-Multilevel Attention Transformer for Rapid Recognition of Pneumonia from Chest X-Ray Images

Reference 22

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Observation 9f4e4587-c380-46cf-b816-dd1ae3e9a323 · outbound

This paper cites Semi-supervised medical image classification with global latent mixing.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Semi-supervised medical image classification with global latent mixing

Reference 24

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Observation 9445f2b9-ee69-4b95-b00f-bf290c310f22 · outbound

This paper cites Revisiting self-supervised visual repre- sentation learning.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Revisiting self-supervised visual repre- sentation learning

Reference 25

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Observation 13d06930-3b09-4ff8-806d-b05e81616269 · outbound

This paper cites The 2005 pascal visual object classes challenge.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels The 2005 pascal visual object classes challenge

Reference 26

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation b092e71a-b524-409e-9c1d-848c620e6731 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Adam: A Method for Stochastic Optimization

Reference 27

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Source-reported events for the cited work

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Observation a9930a5e-60d8-484e-b103-c6ac9ded4bf8 · outbound

This paper cites A texture-based neural network classifier for biometric iden- tification using ocular surface vasculature.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels A texture-based neural network classifier for biometric iden- tification using ocular surface vasculature

Reference 2006

Resolution
verified fuzzy
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Observation bf00d63b-52e2-41e2-ad0d-4b5085dec57c · outbound

This paper cites Enhancement and registration schemes for matching conjunctival vasculature.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Enhancement and registration schemes for matching conjunctival vasculature

Reference 2007

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verified fuzzy
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Source-reported events for the cited work

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Observation 96ec941c-132a-4651-9452-6b05b8e5af62 · outbound

This paper cites A new approach for sclera vein recognition.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels A new approach for sclera vein recognition

Reference 2009

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Source-reported events for the cited work

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Observation f6e2c670-f89d-4e78-a7e5-14aee5f4c376 · outbound

This paper cites Extracting sclera features for cancelable identity verification.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Extracting sclera features for cancelable identity verification

Reference 2010

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 3d2a9dd4-5525-46f4-979f-9c8a1f3a8fcf · outbound

This paper cites Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data

Reference 2012

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Observation c58ac21f-708e-44fa-b882-230ff496b70d · outbound

This paper cites A comprehensive sciera image quality measure.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels A comprehensive sciera image quality measure

Reference 2013

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Source-reported events for the cited work

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Observation a6c7bb00-8e9d-495b-9ad9-7383f788c558 · outbound

This paper cites Sclera vein identification in real time using single board computer.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Sclera vein identification in real time using single board computer

Reference 2014

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Source-reported events for the cited work

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Observation 6cc01302-9a49-4bcf-9e55-eaa59d551f85 · outbound

This paper cites Scleral buckle surgery for primary retinal detachment without posterior vitreous detachment.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Scleral buckle surgery for primary retinal detachment without posterior vitreous detachment

Reference 2015

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Source-reported events for the cited work

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Observation 837968fc-e31a-4ccd-bb28-a8847366ba9b · outbound

This paper cites Semi-supervised learn- ing by disentangling and self-ensembling over stochastic latent space.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Semi-supervised learn- ing by disentangling and self-ensembling over stochastic latent space

Reference 2016

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verified fuzzy
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Source-reported events for the cited work

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Observation 317f9b14-8ed1-4689-a464-e1319b7b18fb · outbound

This paper cites Temporal Ensembling for Semi-Supervised Learning.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Temporal Ensembling for Semi-Supervised Learning

Reference 2017

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Observation 12a3d82a-e8e0-4ef3-9745-62b366286bc2 · outbound

This paper cites U-net: Convolutional networks for biomed- ical image segmentation.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels U-net: Convolutional networks for biomed- ical image segmentation

Reference 2018

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verified fuzzy
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Source-reported events for the cited work

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Observation 6989d76e-a7f8-442c-b6bd-2ab905c111a9 · outbound

This paper cites An image enhancement method based on gamma correction.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels An image enhancement method based on gamma correction

Reference 2019

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 7d9eecb6-1627-41ce-83de-1ea521d08f26 · outbound

This paper cites Sclera- transfuse: Fusing swin transformer and cnn for accurate sclera segmentation.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Sclera- transfuse: Fusing swin transformer and cnn for accurate sclera segmentation

Reference 2021

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verified fuzzy
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Source-reported events for the cited work

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Observation 344dbc36-efa0-46a2-a3f1-9f87aaa353f1 · outbound

This paper cites Foundation Models for Weather and Climate Data Understanding: A Comprehensive Survey.

Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels Foundation Models for Weather and Climate Data Understanding: A Comprehensive Survey

Reference 2023

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.