Paper Citation Record · LEDGER

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features

As of 23 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2608.04379.

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

pith.paper-citation-record.v1
2608.04379 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T18:43:58.191527Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

30 of 30 outbound references displayed

verified exact0
verified fuzzy24
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f7554d0f-cb85-40ca-bbab-53e8287bbdc3 · outbound

This paper cites Atp: Adaptive threshold pruning for efficient data encoding in quantum neural networks.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Atp: Adaptive threshold pruning for efficient data encoding in quantum neural networks

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.702776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2a39422c-db01-47c4-8728-02ed26f3bf74 · outbound

This paper cites Quantum–classical image processing for scene classi- fication.IEEE Sensors Letters, 6(6):1–4, 2022.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Quantum–classical image processing for scene classi- fication.IEEE Sensors Letters, 6(6):1–4, 2022

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.689320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f2f19645-0c27-4afc-bba4-f4dd4d446a97 · outbound

This paper cites Micro- doppler effect in radar: phenomenon, model, and simulation study.IEEE Transactions on Aerospace and electronic sys- tems, 42(1):2–21, 2006.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Micro- doppler effect in radar: phenomenon, model, and simulation study.IEEE Transactions on Aerospace and electronic sys- tems, 42(1):2–21, 2006

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.674289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3bab7844-c3e8-4a7e-976e-d36f2924c81a · outbound

This paper cites Simulating noisy quantum circuits with matrix product density operators.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Simulating noisy quantum circuits with matrix product density operators

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.658357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4abd12c0-09bf-495c-b43d-c1fa41667273 · outbound

This paper cites HQNN-FSP: A Hybrid Classical-Quantum Neural Network for Regression-Based Financial Stock Market Prediction.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features HQNN-FSP: A Hybrid Classical-Quantum Neural Network for Regression-Based Financial Stock Market Prediction

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-08T18:43:57.660351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce749a87-48a1-44e4-b17a-a1eb0d392b92 · outbound

This paper cites Reducing Overfitting in Deep Networks by Decorrelating Representations.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Reducing Overfitting in Deep Networks by Decorrelating Representations

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-08T18:43:57.666252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9357257c-64a9-4e66-93f3-60cfabed3850 · outbound

This paper cites Improv- ing stdp-based visual feature learning with whitening.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Improv- ing stdp-based visual feature learning with whitening

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.643228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 91707286-43c9-4362-9465-d109fac6e629 · outbound

This paper cites Hybrid quantum-classical convolutional neural network model for image classification.IEEE transactions on neural networks and learning systems, 2023.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Hybrid quantum-classical convolutional neural network model for image classification.IEEE transactions on neural networks and learning systems, 2023

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.627147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cd288e6f-96e5-41e9-ad54-3d5c5406ace7 · outbound

This paper cites Deep Convolutional Networks as shallow Gaussian Processes.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Deep Convolutional Networks as shallow Gaussian Processes

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-08T18:43:57.681783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41ff5e46-e79a-4e9c-b04c-3c46aabbadc3 · outbound

This paper cites A hybrid quantum-classical cnn architec- ture for semantic segmentation of radar sounder data.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features A hybrid quantum-classical cnn architec- ture for semantic segmentation of radar sounder data

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.611567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4dc9783c-aab9-4941-a014-1a23af210697 · outbound

This paper cites Quantum convolutional neural network based on varia- tional quantum circuits.Optics Communications, 550:129993,.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Quantum convolutional neural network based on varia- tional quantum circuits.Optics Communications, 550:129993,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.596087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation db0850e3-0a1c-47ed-aa9c-15f2a2043c74 · outbound

This paper cites H-qnn: A hybrid quantum–classical neural network for im- proved binary image classification.AI, 5(3):1462–1481, 2024.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features H-qnn: A hybrid quantum–classical neural network for im- proved binary image classification.AI, 5(3):1462–1481, 2024

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.579783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6004378b-1e15-4a0d-a6fe-fdf404974510 · outbound

This paper cites Supervised learning with quantum-enhanced fea- ture spaces.Nature, 567(7747):209–212, 2019.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Supervised learning with quantum-enhanced fea- ture spaces.Nature, 567(7747):209–212, 2019

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.561067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 32ac7236-4fa9-4a82-be66-527959d6b49c · outbound

This paper cites Quantum convo- lutional neural network for classical data classification.Quan- tum Machine Intelligence, 4(1):3, 2022.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Quantum convo- lutional neural network for classical data classification.Quan- tum Machine Intelligence, 4(1):3, 2022

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.545330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 69806118-da1a-408a-8b85-14c9c1ad8e31 · outbound

This paper cites Quan- tum machine learning beyond kernel methods.Nature Com- munications, 14(1):517, 2023.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Quan- tum machine learning beyond kernel methods.Nature Com- munications, 14(1):517, 2023

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.529671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 361bc81b-6622-4693-bddb-4fae35238bda · outbound

This paper cites Human detection and activity classification based on micro-doppler signatures using deep convolutional neural networks.IEEE geoscience and remote sensing letters, 13(1):8–12, 2015.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Human detection and activity classification based on micro-doppler signatures using deep convolutional neural networks.IEEE geoscience and remote sensing letters, 13(1):8–12, 2015

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.513711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3303fc4d-f6ea-439a-874e-1ee4bfa93dfd · outbound

This paper cites Human detection by neural networks using a low-cost short-range doppler radar sensor.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Human detection by neural networks using a low-cost short-range doppler radar sensor

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.498748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation bd97c99a-173f-49e5-979e-c7836c9f4365 · outbound

This paper cites A flexible representation of quantum images for polynomial preparation, image compression, and processing operations.Quantum Information Processing, 10(1):63–84, 2011.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features A flexible representation of quantum images for polynomial preparation, image compression, and processing operations.Quantum Information Processing, 10(1):63–84, 2011

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.483450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 400d6c01-6dcf-43fc-a71c-854bf9659110 · outbound

This paper cites Radar hrrp target recognition based on hybrid quantum neural networks.IEEE Transactions on Aerospace and Electronic Systems, 2025.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Radar hrrp target recognition based on hybrid quantum neural networks.IEEE Transactions on Aerospace and Electronic Systems, 2025

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.467093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 35907d04-672b-4994-8111-c343dbc8f2e6 · outbound

This paper cites Barren plateaus in quan- tum neural network training landscapes.Nature communica- tions, 9(1):4812, 2018.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Barren plateaus in quan- tum neural network training landscapes.Nature communica- tions, 9(1):4812, 2018

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.450108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c16413bc-ab70-4cbe-90ba-9c9c7402c01b · outbound

This paper cites Cambridge university press,.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Cambridge university press,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T18:43:57.828974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42dde3f0-9197-404a-8c61-8315191d8545 · outbound

This paper cites Switchable whitening for deep representation learning.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Switchable whitening for deep representation learning

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.419630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0197b76c-4b45-4ecc-a8d6-c88bde7c6703 · outbound

This paper cites Quantum computing in the nisq era and beyond.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Quantum computing in the nisq era and beyond

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-08T18:43:57.909515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0dc911c4-8120-4d84-ad26-7fcf2d276956 · outbound

This paper cites Hybrid quantum-classical graph neural networks for tumor classification in digital pathology.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Hybrid quantum-classical graph neural networks for tumor classification in digital pathology

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.389190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d31f7479-e24f-4e12-aeb7-b77f9e86457c · outbound

This paper cites Regularizing CNNs with Locally Constrained Decorrelations.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Regularizing CNNs with Locally Constrained Decorrelations

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-08T18:43:58.033231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7e9d096-6b82-498c-b1fe-f19e57587e09 · outbound

This paper cites Evaluating analytic gradients on quan- tum hardware.Physical Review A, 99(3):032331, 2019.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Evaluating analytic gradients on quan- tum hardware.Physical Review A, 99(3):032331, 2019

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.370148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e5260bad-dbe0-49a3-9c06-488aa6a4b373 · outbound

This paper cites Ex- pressibility and entangling capability of parameterized quan- tum circuits for hybrid quantum-classical algorithms.Ad- vanced Quantum Technologies, 2(12):1900070, 2019.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Ex- pressibility and entangling capability of parameterized quan- tum circuits for hybrid quantum-classical algorithms.Ad- vanced Quantum Technologies, 2(12):1900070, 2019

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.351239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 330492de-7954-4a17-bd50-144ce6367a24 · outbound

This paper cites Transition role of entangled data in quantum machine learning.Nature Communications, 15(1): 3716, 2024.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Transition role of entangled data in quantum machine learning.Nature Communications, 15(1): 3716, 2024

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.331572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 40c7a4d8-bc9e-4424-93f0-8b302eb19358 · outbound

This paper cites Barlow twins: Self-supervised learning via redundancy reduction.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features Barlow twins: Self-supervised learning via redundancy reduction

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.314241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f3c21486-b2dd-4f97-ac32-fe679a2a7063 · outbound

This paper cites The extraction of micro-doppler sig- nal with emd algorithm for radar-based small uavs’ detection.

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features The extraction of micro-doppler sig- nal with emd algorithm for radar-based small uavs’ detection

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:43:58.296972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.