Paper Citation Record · LEDGER

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images

As of 20 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 1 inbound Pith citation observation for arXiv:2508.00135.

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

pith.paper-citation-record.v1
2508.00135 v2

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:24:10.644677Z

measured 29 of 29 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:24:10.559057Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T10:24:11.819761Z

Reference resolution

28 of 28 outbound references displayed

verified exact16
verified fuzzy1
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch6

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 138870ad-686f-4712-a072-41e09f0b3b23 · outbound

This paper cites Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-06T10:24:11.823604Z

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.

Observation 9dc38bf5-1472-41cc-902a-df4abcc8256c · outbound

This paper cites an unresolved cited work.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Unresolved cited work

Reference 3

Resolution: verified exact; raw_fallback, observed 2026-08-06T10:24:11.807040Z

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.

Observation 4a26ed54-97b6-4965-9672-f0d4e3830ef9 · outbound

This paper cites La; Bisogni, C.; Cascone, L.; Narducci, F.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images La; Bisogni, C.; Cascone, L.; Narducci, F

Reference 11

Resolution: verified exact; doi, observed 2026-08-06T10:24:10.774259Z

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.

Observation 43183e36-837a-4cee-916d-696cff9de66a · outbound

This paper cites A Comparative Study on the Importance of Each Face Part in Facial Gender Recognition via Convolutional Neural Networks.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images A Comparative Study on the Importance of Each Face Part in Facial Gender Recognition via Convolutional Neural Networks

Reference 12

Resolution: verified exact; raw_fallback, observed 2026-08-06T10:24:11.718695Z

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.

Observation 965014de-986d-4a6c-979e-d47f79788188 · outbound

This paper cites an unresolved cited work.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Unresolved cited work

Reference 13

Resolution: verified exact; doi, observed 2026-08-06T10:24:10.763608Z

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.

Observation e82d9e4d-e9fb-4742-aa78-047374c343d1 · outbound

This paper cites A.; Aly, S.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images A.; Aly, S

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T10:24:10.576719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 827b9a63-b1ac-4572-8706-09d197868cbd · outbound

This paper cites an unresolved cited work.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Unresolved cited work

Reference 15

Resolution: verified exact; doi, observed 2026-08-06T10:24:10.754077Z

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.

Observation 8b90fe5e-a9e6-40f1-88a3-250a522f3a8a · outbound

This paper cites Relevant Features for Gender Classification in NIR Periocular Images.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Relevant Features for Gender Classification in NIR Periocular Images

Reference 16

Resolution: verified exact; raw_fallback, observed 2026-08-06T10:24:11.589244Z

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.

Observation 213479c9-b15f-4dbe-b212-4464f657f5a1 · outbound

This paper cites Predicting Gender from Iris Texture May Be Harder than It Seems.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Predicting Gender from Iris Texture May Be Harder than It Seems

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T10:24:10.585587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46c5c6d6-dfa0-4482-9157-c99c4741aa4d · outbound

This paper cites Sex-Classification from Cellphones Periocular Iris Images.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Sex-Classification from Cellphones Periocular Iris Images

Reference 18

Resolution: verified exact; doi, observed 2026-08-06T10:24:10.744241Z

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.

Observation 84fcc9b2-8b42-422a-8dff-149dd4e322f6 · outbound

This paper cites CNN -Based Gender Classification in near - Infrared Periocular Images.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images CNN -Based Gender Classification in near - Infrared Periocular Images

Reference 19

Resolution: verified exact; doi, observed 2026-08-06T10:24:10.733649Z

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.

Observation a5070e13-f364-451f-a297-4951733d016e · outbound

This paper cites Generalizable Deep Features for Ocular Biometrics.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Generalizable Deep Features for Ocular Biometrics

Reference 20

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T10:24:11.455733Z

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.

Observation edc0d153-4b46-4111-a89e-bbc030dc4d66 · outbound

This paper cites an unresolved cited work.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Unresolved cited work

Reference 21

Resolution: verified exact; doi, observed 2026-08-06T10:24:10.721727Z

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.

Observation 91784851-be85-41f6-9c32-5ad6438b13aa · outbound

This paper cites C.; Roth, H.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images C.; Roth, H

Reference 22

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T10:24:11.377995Z

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.

Observation 8085a96e-ca57-4339-9a61-df144d12bea3 · outbound

This paper cites A Review on Deep Convolutional Neural Networks.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images A Review on Deep Convolutional Neural Networks

Reference 23

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T10:24:11.312164Z

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.

Observation dd70041a-b0f0-4ff8-8db8-84b3980badfd · outbound

This paper cites A Framework for Designing the Architectures of Deep Convolutional Neura l Networks.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images A Framework for Designing the Architectures of Deep Convolutional Neura l Networks

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:24:11.846493Z

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.

Observation a7386722-3ed1-4ee6-a93d-0fcb7af82a9b · outbound

This paper cites Human Detection and Activity Classification Based on Micro -Doppler Signatures Using Deep Convolutional Neural Networks.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Human Detection and Activity Classification Based on Micro -Doppler Signatures Using Deep Convolutional Neural Networks

Reference 25

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T10:24:11.248092Z

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.

Observation acd5aefe-3d7a-4336-b377-befabeff9d88 · outbound

This paper cites Parametric Exponential Linear Unit for Deep Convolutional Neural Networks.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Parametric Exponential Linear Unit for Deep Convolutional Neural Networks

Reference 26

Resolution: verified exact; raw_fallback, observed 2026-08-06T10:24:11.175839Z

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.

Observation 3b97567b-f8b4-4c79-b062-da6872dd463e · outbound

This paper cites Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T10:24:10.620492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc43f124-de01-4a0e-a6f9-195490e3327b · outbound

This paper cites Improved Convolutional Neural Network Based on Fast Exponentially Linear Unit Activation Function.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Improved Convolutional Neural Network Based on Fast Exponentially Linear Unit Activation Function

Reference 28

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T10:24:11.108988Z

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.

Observation 67fcbfc9-dc5c-447e-aefb-87ef34518f5c · outbound

This paper cites S.; Ludermir, T.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images S.; Ludermir, T

Reference 29

Resolution: verified exact; doi, observed 2026-08-06T10:24:10.692233Z

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.

Observation 3f7d8e82-cbfe-4fa0-b2cc-e5f6f2d05af6 · outbound

This paper cites D.; Adjailia, F.; Sincak, P.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images D.; Adjailia, F.; Sincak, P

Reference 30

Resolution: verified exact; raw_fallback, observed 2026-08-06T10:24:11.026620Z

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.

Observation f858edea-1998-4d71-936b-9e4929416963 · outbound

This paper cites A Survey on Activation Functions and their relation with Xavier and He Normal Initialization.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images A Survey on Activation Functions and their relation with Xavier and He Normal Initialization

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T10:24:10.633085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1da95810-d269-45e0-ac6e-5ea1b2c5e0ea · outbound

This paper cites an unresolved cited work.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-08-06T10:24:11.834722Z

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.

Observation 06f2287a-ae9b-4d10-8515-8a37203274ae · outbound

This paper cites an unresolved cited work.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Unresolved cited work

Reference 33

Resolution: verified exact; doi, observed 2026-08-06T10:24:10.673796Z

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.

Observation 0d46c87b-d4da-4bdc-a5af-b1088dd19ca3 · outbound

This paper cites an unresolved cited work.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Unresolved cited work

Reference 34

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T10:24:10.960267Z

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.

Observation e13fcd81-eba3-4226-80f0-4d4969bc14f6 · outbound

This paper cites Female and Male Eyes.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Female and Male Eyes

Reference 35

Resolution: verified exact; raw_fallback, observed 2026-08-06T10:24:10.887995Z

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.

Observation 0d1dee18-3baf-4b1f-aa56-462abc2c238c · outbound

This paper cites an unresolved cited work.

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images Unresolved cited work

Reference 242

Resolution: verified exact; doi, observed 2026-08-06T10:24:10.710664Z

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.

Pith citing papers

Observation 138870ad-686f-4712-a072-41e09f0b3b23 · inbound