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Paper Citation Record · LEDGER

Lightweight Convolutional Neural Networks for Retinal Disease Classification

As of 8 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2506.03186.

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

pith.paper-citation-record.v1
2506.03186 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:21:36.692115Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

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

Source: cited_works

Reference resolution

24 of 24 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0c1df00a-8ebe-4df1-bb07-68e6f752379e · outbound

This paper cites Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs,

Reference 1

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Observation d11c594e-ee9f-4782-9f0f-6b7a7bca7770 · outbound

This paper cites Classification of multiple retinal disorders from enhanced fundus images using semi -supervised GAN,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification Classification of multiple retinal disorders from enhanced fundus images using semi -supervised GAN,

Reference 2

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This paper cites Artificial intelligence based -improving reservoir management: An Attention -Guided Fusion Model for predicting injector –producer connectivity,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification Artificial intelligence based -improving reservoir management: An Attention -Guided Fusion Model for predicting injector –producer connectivity,

Reference 3

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Observation 549e6edb-cf06-4629-9d03-921b4b8cde47 · outbound

This paper cites Employing the Concept of Stacking Ensemble Learning to Generate Deep Dream Images Using Multiple CNN Variants,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification Employing the Concept of Stacking Ensemble Learning to Generate Deep Dream Images Using Multiple CNN Variants,

Reference 4

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Observation 206f07fd-6570-4fa6-8e04-af1ac4bf1398 · outbound

This paper cites A Comparative Study of IDS-Based Deep Learning Models for IoT Network,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification A Comparative Study of IDS-Based Deep Learning Models for IoT Network,

Reference 5

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Observation 83641a5b-cd6b-4872-98bf-6ded32067523 · outbound

This paper cites Automatic classification of retinal diseases with transfer learning -based lightweight convolutional neural network,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification Automatic classification of retinal diseases with transfer learning -based lightweight convolutional neural network,

Reference 6

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Observation f87954dc-57d3-4b85-b9ed-24215fa9b69b · outbound

This paper cites Osteoporosis detection using convolutional neural network based on dual -energy X -ray absorptiometry images,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification Osteoporosis detection using convolutional neural network based on dual -energy X -ray absorptiometry images,

Reference 7

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Observation 66ee922c-2f44-4020-bc39-4cecb59aeaec · outbound

This paper cites Optimized deep convolutional neural networks for identification of macular diseases from optical coherence tomography images,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification Optimized deep convolutional neural networks for identification of macular diseases from optical coherence tomography images,

Reference 8

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Observation 8136b8b2-e09a-4695-832e-d8bed185e95f · outbound

This paper cites A convolutional neural network for the screening and staging of diabetic retinopathy,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification A convolutional neural network for the screening and staging of diabetic retinopathy,

Reference 9

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Observation f183b653-d971-476f-a8b5-78b40e7b3d0b · outbound

This paper cites Classification of retinal images based on convolutional neural network,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification Classification of retinal images based on convolutional neural network,

Reference 10

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Observation 72e4e7e1-f362-4118-a085-ba7b1fbedda2 · outbound

This paper cites Retina diseases diagnosis using deep learning,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification Retina diseases diagnosis using deep learning,

Reference 11

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Observation 856a5a0e-49c2-4cf2-afe1-2087c8e3afa1 · outbound

This paper cites Multi categorical of common eye disease detect using convolutional neural network: a transfer learning approach,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification Multi categorical of common eye disease detect using convolutional neural network: a transfer learning approach,

Reference 12

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Observation 1df9f840-62db-41be-87f3-cdf0cd352741 · outbound

This paper cites Explainable Convolutional Neural Networks for Retinal Fundus Classification and Cutting-Edge Segmentation Models for Retinal Blood Vessels from Fundus Images.

Lightweight Convolutional Neural Networks for Retinal Disease Classification Explainable Convolutional Neural Networks for Retinal Fundus Classification and Cutting-Edge Segmentation Models for Retinal Blood Vessels from Fundus Images

Reference 13

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Observation cd8da642-5887-4484-a751-3ce895f085e4 · outbound

This paper cites Deep Learning Based Multi -Class Eye Disease Classification: Enhancing Vision Health Diagnosis,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification Deep Learning Based Multi -Class Eye Disease Classification: Enhancing Vision Health Diagnosis,

Reference 14

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Observation c932154a-d6ce-45c6-99d7-32cbd0279596 · outbound

This paper cites Instantaneous Classification and Localization of Eye Diseases via Artificial Intelligence,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification Instantaneous Classification and Localization of Eye Diseases via Artificial Intelligence,

Reference 15

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Observation bc605fca-4915-498f-bbee-012bf9609d70 · outbound

This paper cites Retinal fundus multi -disease image dataset (rfmid): A dataset for multi-disease detection research,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification Retinal fundus multi -disease image dataset (rfmid): A dataset for multi-disease detection research,

Reference 16

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Observation e922461d-da00-4122-8f55-62f68d76b659 · outbound

This paper cites A Scalable and Generalised Deep Learning Framework for Anomaly Detection in Surveillance Videos,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification A Scalable and Generalised Deep Learning Framework for Anomaly Detection in Surveillance Videos,

Reference 17

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Observation a89fea78-1a59-4d37-887d-09519ea93759 · outbound

This paper cites ATD Learning: A secure, smart, and decentralised learning method for big data environments,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification ATD Learning: A secure, smart, and decentralised learning method for big data environments,

Reference 18

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This paper cites Heart Attack Prediction by Integrating Independent Component Analysis with Machine Learning Classifiers,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification Heart Attack Prediction by Integrating Independent Component Analysis with Machine Learning Classifiers,

Reference 19

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This paper cites Multi -label classification of fundus images with efficientnet,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification Multi -label classification of fundus images with efficientnet,

Reference 20

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Lightweight Convolutional Neural Networks for Retinal Disease Classification Unresolved cited work

Reference 21

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Observation 50fad13d-3f9e-4be7-a213-fcbdaa586036 · outbound

This paper cites ViLReF: An Expert Knowledge Enabled Vision - Language Retinal Foundation Model,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification ViLReF: An Expert Knowledge Enabled Vision - Language Retinal Foundation Model,

Reference 22

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This paper cites A deep learning framework for the early detection of multi-retinal diseases,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification A deep learning framework for the early detection of multi-retinal diseases,

Reference 23

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Observation da28f73d-c9b2-497c-928d-2ee530e2f06e · outbound

This paper cites Deep hybrid architecture with stacked ensemble learning for binary classification of retinal disease,.

Lightweight Convolutional Neural Networks for Retinal Disease Classification Deep hybrid architecture with stacked ensemble learning for binary classification of retinal disease,

Reference 24

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Pith citing papers

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