Paper Citation Record · LEDGER

Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2411.18622.

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

pith.paper-citation-record.v1
2411.18622 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:55:48.099963Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-10T23:26:40.053179Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c7a4cd5e-0249-459c-b955-279400bd2185 · inbound

Dynamic User Interface Generation for Enhanced Human-Computer Interaction Using Variational Autoencoders cites this paper.

Dynamic User Interface Generation for Enhanced Human-Computer Interaction Using Variational Autoencoders Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T12:12:20.020910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd6c1c4c-3a73-4388-9615-25e0f64ce625 · inbound

Machine Learning Techniques for Pattern Recognition in High-Dimensional Data Mining cites this paper.

Machine Learning Techniques for Pattern Recognition in High-Dimensional Data Mining Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T11:18:30.892202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fc6f42d-22ef-4762-b6aa-78562a3149a7 · inbound

Adaptive User Interface Generation Through Reinforcement Learning: A Data-Driven Approach to Personalization and Optimization cites this paper.

Adaptive User Interface Generation Through Reinforcement Learning: A Data-Driven Approach to Personalization and Optimization Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T10:18:14.575183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e71263b7-5b49-4bbd-b4d6-91978a663552 · inbound

Dynamic Scheduling Strategies for Resource Optimization in Computing Environments cites this paper.

Dynamic Scheduling Strategies for Resource Optimization in Computing Environments Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T05:40:19.740543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 022b3b19-84de-46b7-b196-b26fb21b4455 · inbound

Collaborative Optimization in Financial Data Mining Through Deep Learning and ResNeXt cites this paper.

Collaborative Optimization in Financial Data Mining Through Deep Learning and ResNeXt Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T05:38:37.626822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37aaf06c-c4bd-4e6b-ae79-815b11623c52 · inbound

Computer Vision-Driven Gesture Recognition: Toward Natural and Intuitive Human-Computer cites this paper.

Computer Vision-Driven Gesture Recognition: Toward Natural and Intuitive Human-Computer Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T04:50:46.909587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5b00f41-c46e-41bd-ae1d-035dafbd8b1a · inbound

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets cites this paper.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T00:39:35.511499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45b15cfd-f9c2-48a2-8eff-62cc7e24160b · inbound

Deep Learning in Image Classification: Evaluating VGG19's Performance on Complex Visual Data cites this paper.

Deep Learning in Image Classification: Evaluating VGG19's Performance on Complex Visual Data Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-10T23:26:40.059396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ed9e0c88-e253-4738-a7dd-f6d2cb27762d · inbound

AI-Driven Health Monitoring of Distributed Computing Architecture: Insights from XGBoost and SHAP cites this paper.

AI-Driven Health Monitoring of Distributed Computing Architecture: Insights from XGBoost and SHAP Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T14:55:48.099963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.