Paper Citation Record · LEDGER

AdaptoVision: A Multi-Resolution Image Recognition Model for Robust and Scalable Classification

As of 22 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2504.12652.

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

pith.paper-citation-record.v1
2504.12652 v2

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:30:11.045288Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

13 of 13 outbound references displayed

verified exact0
verified fuzzy2
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 86753272-ed59-48f7-b0d5-2c16749984f3 · outbound

This paper cites AutoAugment: Learning Augmentation Policies from Data.

AdaptoVision: A Multi-Resolution Image Recognition Model for Robust and Scalable Classification AutoAugment: Learning Augmentation Policies from Data

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T12:30:11.025079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e579fe4c-b45a-449f-8bec-88adcf7f7771 · outbound

This paper cites Histopathological breast cancer image classification by deep neural network techniques guided by local clustering.BioMed research international, 2018,.

AdaptoVision: A Multi-Resolution Image Recognition Model for Robust and Scalable Classification Histopathological breast cancer image classification by deep neural network techniques guided by local clustering.BioMed research international, 2018,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:30:11.481602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bbb81d16-2dde-4346-9ba6-e1cc99de01c3 · outbound

This paper cites Kassem, Khalid M.

AdaptoVision: A Multi-Resolution Image Recognition Model for Robust and Scalable Classification Kassem, Khalid M

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:30:11.466004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6662e19e-8d07-41c6-9dae-86b4387b6513 · outbound

This paper cites an unresolved cited work.

AdaptoVision: A Multi-Resolution Image Recognition Model for Robust and Scalable Classification Unresolved cited work

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T12:30:11.045288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 342281dd-4374-41f4-9c0c-16173b58ea27 · outbound

This paper cites Improving neural networks by preventing co-adaptation of feature detectors.

AdaptoVision: A Multi-Resolution Image Recognition Model for Robust and Scalable Classification Improving neural networks by preventing co-adaptation of feature detectors

Reference 1995

Resolution: unresolved; no resolver link, observed 2026-08-16T12:30:10.992595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22ce8833-499d-42e6-ad40-2dfa4c78d207 · outbound

This paper cites Attentive CutMix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification.

AdaptoVision: A Multi-Resolution Image Recognition Model for Robust and Scalable Classification Attentive CutMix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification

Reference 2010

Resolution: unresolved; no resolver link, observed 2026-08-16T12:30:11.016924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f53c232-8ca2-4409-b68e-62bde3cf2c53 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

AdaptoVision: A Multi-Resolution Image Recognition Model for Robust and Scalable Classification Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 2012

Resolution: unresolved; no resolver link, observed 2026-08-16T12:30:10.998067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddd4d5ef-618e-4d44-bb7a-5bbe2a1d1003 · outbound

This paper cites Marc Combalia, Noel C.

AdaptoVision: A Multi-Resolution Image Recognition Model for Robust and Scalable Classification Marc Combalia, Noel C

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-16T12:30:11.012619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a94d083-5aba-4fac-b3b4-5c2becdc3136 · outbound

This paper cites Highway Networks.

AdaptoVision: A Multi-Resolution Image Recognition Model for Robust and Scalable Classification Highway Networks

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-16T12:30:11.002785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68f3b943-ee57-4da1-aad9-8aedb985a2db · outbound

This paper cites CoCa: Contrastive Captioners are Image-Text Foundation Models.

AdaptoVision: A Multi-Resolution Image Recognition Model for Robust and Scalable Classification CoCa: Contrastive Captioners are Image-Text Foundation Models

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-16T12:30:11.007552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5714bbf3-6f0d-43a9-acd3-d9634bbb2e91 · outbound

This paper cites MobileNetV2: Inverted Residuals and Linear Bottlenecks.

AdaptoVision: A Multi-Resolution Image Recognition Model for Robust and Scalable Classification MobileNetV2: Inverted Residuals and Linear Bottlenecks

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-16T12:30:11.029142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 008171e7-8a47-4b53-84fa-437ed3412269 · outbound

This paper cites an unresolved cited work.

AdaptoVision: A Multi-Resolution Image Recognition Model for Robust and Scalable Classification Unresolved cited work

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-16T12:30:11.021394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f00175eb-36af-4356-8632-10606112bbce · outbound

This paper cites doi:https://doi.org/10.1016/j.iswa.2022.200066.

AdaptoVision: A Multi-Resolution Image Recognition Model for Robust and Scalable Classification doi:https://doi.org/10.1016/j.iswa.2022.200066

Reference 2022

Resolution: metadata mismatch; raw_fallback, observed 2026-08-16T12:30:11.218511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

No inbound Pith citation observations are available.