Paper Citation Record · LEDGER

STC-Net: Electroluminescence-Based Solar Cell Crack Segmentation for Power Loss Estimation

As of 17 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2608.01714.

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

pith.paper-citation-record.v1
2608.01714 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T22:21:17.614484Z

measured 14 of 14 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

14 of 14 outbound references displayed

verified exact0
verified fuzzy12
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 24aff15f-c912-417d-a225-550221eed9c8 · outbound

This paper cites an unresolved cited work.

STC-Net: Electroluminescence-Based Solar Cell Crack Segmentation for Power Loss Estimation Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-04T22:21:17.853295Z

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.

Observation 3e5c14fc-b610-48b6-b6b1-c28aae78b897 · outbound

This paper cites Segmentation of cell-level anomalies in electroluminescence images of photovoltaic modules,.

STC-Net: Electroluminescence-Based Solar Cell Crack Segmentation for Power Loss Estimation Segmentation of cell-level anomalies in electroluminescence images of photovoltaic modules,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:21:17.839428Z

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.

Observation b875700d-c46b-43ab-b581-a4c18e73c100 · outbound

This paper cites Attention classification-and-segmentation network for micro-crack anomaly detection of photovoltaic module cells,.

STC-Net: Electroluminescence-Based Solar Cell Crack Segmentation for Power Loss Estimation Attention classification-and-segmentation network for micro-crack anomaly detection of photovoltaic module cells,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:21:17.825046Z

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.

Observation 68d49503-50d8-4b9a-ac9e-92458797c492 · outbound

This paper cites Analysis of luminescence images applying pattern recognition techniques,.

STC-Net: Electroluminescence-Based Solar Cell Crack Segmentation for Power Loss Estimation Analysis of luminescence images applying pattern recognition techniques,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:21:17.809585Z

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.

Observation 913190eb-7067-4647-86f2-97d2cfd5e49b · outbound

This paper cites Automatic classification of defective photovoltaic module cells in electroluminescence images,.

STC-Net: Electroluminescence-Based Solar Cell Crack Segmentation for Power Loss Estimation Automatic classification of defective photovoltaic module cells in electroluminescence images,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:21:17.795170Z

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.

Observation 93c92e6d-87ba-4b1b-8394-070f3b2a4e82 · outbound

This paper cites Automated pipeline for photovoltaic module electroluminescence image processing and degradation feature classification,.

STC-Net: Electroluminescence-Based Solar Cell Crack Segmentation for Power Loss Estimation Automated pipeline for photovoltaic module electroluminescence image processing and degradation feature classification,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:21:17.780144Z

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.

Observation 05a57e3c-8040-4651-bfa0-26d30a8e200a · outbound

This paper cites Detection of surface defects on solar cells by fusing multi-channel convolution neural networks,.

STC-Net: Electroluminescence-Based Solar Cell Crack Segmentation for Power Loss Estimation Detection of surface defects on solar cells by fusing multi-channel convolution neural networks,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:21:17.764639Z

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.

Observation 8710b4f6-db5c-454b-8aa6-9de126ac0971 · outbound

This paper cites Deep learning-based automatic detection of multitype defects in photovoltaic modules and application in real production line,.

STC-Net: Electroluminescence-Based Solar Cell Crack Segmentation for Power Loss Estimation Deep learning-based automatic detection of multitype defects in photovoltaic modules and application in real production line,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:21:17.749204Z

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.

Observation eb1e7485-e3ca-472c-8470-9bc492b3de1a · outbound

This paper cites Defect object detection algorithm for electroluminescence image defects of photovoltaic modules based on deep learning,.

STC-Net: Electroluminescence-Based Solar Cell Crack Segmentation for Power Loss Estimation Defect object detection algorithm for electroluminescence image defects of photovoltaic modules based on deep learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:21:17.732537Z

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.

Observation 2b062fc0-bd15-4a4c-9d25-9fbce368f001 · outbound

This paper cites Encoder– decoder semantic segmentation models for electroluminescence images of thin-film photovoltaic modules,.

STC-Net: Electroluminescence-Based Solar Cell Crack Segmentation for Power Loss Estimation Encoder– decoder semantic segmentation models for electroluminescence images of thin-film photovoltaic modules,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:21:17.717287Z

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.

Observation a6096aca-23e0-4b2f-a563-5dd84769fd95 · outbound

This paper cites Deep- learning-based pipeline for module power prediction from electrolu- minescense measurements,.

STC-Net: Electroluminescence-Based Solar Cell Crack Segmentation for Power Loss Estimation Deep- learning-based pipeline for module power prediction from electrolu- minescense measurements,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:21:17.702135Z

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.

Observation c7c39402-a8e8-45aa-a2ec-baae7df121f4 · outbound

This paper cites An enhanced algorithm for cell-level anomaly segmentation in photovoltaic solar panels using electroluminescence imaging,.

STC-Net: Electroluminescence-Based Solar Cell Crack Segmentation for Power Loss Estimation An enhanced algorithm for cell-level anomaly segmentation in photovoltaic solar panels using electroluminescence imaging,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:21:17.685350Z

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.

Observation 4ca0e914-4491-4df3-831a-ddbc395ba58e · outbound

This paper cites Pvel-ad: A large-scale open-world dataset for photovoltaic cell anomaly detection,.

STC-Net: Electroluminescence-Based Solar Cell Crack Segmentation for Power Loss Estimation Pvel-ad: A large-scale open-world dataset for photovoltaic cell anomaly detection,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:21:17.669545Z

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.

Observation 6114dc05-1211-42e5-b583-2e4b0b5c0015 · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

STC-Net: Electroluminescence-Based Solar Cell Crack Segmentation for Power Loss Estimation Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T22:21:17.614484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.