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Paper Citation Record · LEDGER

MambaOutRS: A Hybrid CNN-Fourier Architecture for Remote Sensing Image Classification

As of 9 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2506.19561.

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

pith.paper-citation-record.v1
2506.19561 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:11:45.553123Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

16 of 16 outbound references displayed

  • verified exact0
  • verified fuzzy12
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d4e9be47-22da-4a67-a50f-fc8443c01721 · outbound

This paper cites Machine learning in modelling land-use and land cover-change (lulcc): Current status, challenges and prospects.

MambaOutRS: A Hybrid CNN-Fourier Architecture for Remote Sensing Image Classification Machine learning in modelling land-use and land cover-change (lulcc): Current status, challenges and prospects

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:11:47.337235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:11:43.993288Z digest=sha256:f1e6d470e5f971bdad840f7b0eefcdf9624c67b6a9116806e6fb1984e0602929

Observation 1e115694-0346-4482-a07e-b664e3d8d0df · outbound

This paper cites Pure data correction enhancing remote sensing image classification with a lightweight ensemble model.

MambaOutRS: A Hybrid CNN-Fourier Architecture for Remote Sensing Image Classification Pure data correction enhancing remote sensing image classification with a lightweight ensemble model

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:11:47.166699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:11:44.108436Z digest=sha256:8595227d06ae66740ba10832ecc7c8f757c6dc4f93caae2629d13781dae69ca5

Observation 32e6d1e2-df92-4182-953f-74f63051757b · outbound

This paper cites Combining kan with cnn: Konvnext’s performance in remote sensing and patent insights.

MambaOutRS: A Hybrid CNN-Fourier Architecture for Remote Sensing Image Classification Combining kan with cnn: Konvnext’s performance in remote sensing and patent insights

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:11:47.005684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:11:44.231581Z digest=sha256:0cb9c17d1dad303025ed937691731068019fea7285e1003874f16d45cd4eb169

Observation 5e4b8f42-d9a3-4c71-8658-08c7d65a2d3a · outbound

This paper cites Rsmamba: Remote sensing image classification with state space model.

MambaOutRS: A Hybrid CNN-Fourier Architecture for Remote Sensing Image Classification Rsmamba: Remote sensing image classification with state space model

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:11:46.861745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:11:44.322321Z digest=sha256:2f076346481f042cb3e3ecd93e1c4264656d8262c00e1838aa6c3315d609075d

Observation 61cfdd02-5c49-443a-83fb-5995d7cee5ca · outbound

This paper cites Remote sensing image classification using deep learning.

MambaOutRS: A Hybrid CNN-Fourier Architecture for Remote Sensing Image Classification Remote sensing image classification using deep learning

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:11:46.730589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:11:44.442846Z digest=sha256:499516f0aa940dffe8ea5927bab909f7ed6fce863b31091f044a8224a4a204ff

Observation e44b3770-db65-4094-9b4a-c9362a3a536f · outbound

This paper cites Review of vision transformer models for remote sensing image scene classification.

MambaOutRS: A Hybrid CNN-Fourier Architecture for Remote Sensing Image Classification Review of vision transformer models for remote sensing image scene classification

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:11:46.610057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:11:44.524456Z digest=sha256:778b4fa917bc0ab58154055b4fe4ed9fdd498947ee3e2b004eae766929059bf7

Observation c0375b5a-1f71-4d32-963b-47ca3cc48314 · outbound

This paper cites Kolmogorov-Arnold Network for Satellite Image Classification in Remote Sensing.

MambaOutRS: A Hybrid CNN-Fourier Architecture for Remote Sensing Image Classification Kolmogorov-Arnold Network for Satellite Image Classification in Remote Sensing

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T23:11:44.633339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:11:44.633339Z digest=sha256:a18d5e636c90cd28ba692423ee14d9f8fbbe082319627cb9f68a1d12992341b6

Observation 3d0208ae-d728-45f3-89a8-ade8dda22a21 · outbound

This paper cites Vivit-prob: A radar echo extrapolation model based on video vision transformer and spatiotemporal sparse attention.

MambaOutRS: A Hybrid CNN-Fourier Architecture for Remote Sensing Image Classification Vivit-prob: A radar echo extrapolation model based on video vision transformer and spatiotemporal sparse attention

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:11:46.468317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:11:44.749656Z digest=sha256:aa243cd80e364985e34366921bb581de17891296c018e712219b6ef9dc9408d2

Observation db30c953-3490-408e-9f6e-42856db1ec76 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

MambaOutRS: A Hybrid CNN-Fourier Architecture for Remote Sensing Image Classification Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T23:11:44.868546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:11:44.868546Z digest=sha256:d88d0c810ca62f10ccf5575f87750c93e0110dbb5522ee38ac8507483888418a

Observation cb973502-4494-47ef-b70a-27c6de870c28 · outbound

This paper cites Vision Mamba: A Comprehensive Survey and Taxonomy.

MambaOutRS: A Hybrid CNN-Fourier Architecture for Remote Sensing Image Classification Vision Mamba: A Comprehensive Survey and Taxonomy

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T23:11:45.025725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:11:45.025725Z digest=sha256:f6d3224dcfcecfb45a63c5f3792577f3819321e7db909cb7bfd0330406cb1a85

Observation b8505967-42ad-4a2b-b49f-69bb56885feb · outbound

This paper cites Mambavision: A hybrid mamba-transformer vision backbone.

MambaOutRS: A Hybrid CNN-Fourier Architecture for Remote Sensing Image Classification Mambavision: A hybrid mamba-transformer vision backbone

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:11:46.315230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:11:45.148407Z digest=sha256:f66fc629015afcda76b00def10633972d0b79ff2711ad8a62393480f1660663e

Observation 7c68e015-0a02-45c5-b168-c3d2ff3094ed · outbound

This paper cites Mambaout: Do we really need mamba for vision? In Proceedings of the Computer Vision and Pattern Recognition Conference, pages 4484--4496, 2025.

MambaOutRS: A Hybrid CNN-Fourier Architecture for Remote Sensing Image Classification Mambaout: Do we really need mamba for vision? In Proceedings of the Computer Vision and Pattern Recognition Conference, pages 4484--4496, 2025

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:11:46.184598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:11:45.248768Z digest=sha256:809abc4fc923bf92536e2b97aa530e681d36b2f5491dae8bb488f2cf7eaf22d7

Observation cf11985b-8b6c-4ae0-84c6-f5fb47d86dee · outbound

This paper cites Aid: A benchmark data set for performance evaluation of aerial scene classification.

MambaOutRS: A Hybrid CNN-Fourier Architecture for Remote Sensing Image Classification Aid: A benchmark data set for performance evaluation of aerial scene classification

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:11:46.011420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:11:45.329253Z digest=sha256:5af87093724af73e3a3e14c7156e398be68981b70911b86c79d2c4e5f1956787

Observation 1da43456-3714-4ebd-9728-9203fdb95a8e · outbound

This paper cites Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification.

MambaOutRS: A Hybrid CNN-Fourier Architecture for Remote Sensing Image Classification Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T23:11:45.441646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:11:45.441646Z digest=sha256:42ad37603da36ab97899e65ebd877740ee31d84871229c705530abb3905fc9b1

Observation e55cc239-fe55-49f4-8176-c54d1fbddc2e · outbound

This paper cites Remote sensing image scene classification: Benchmark and state of the art.

MambaOutRS: A Hybrid CNN-Fourier Architecture for Remote Sensing Image Classification Remote sensing image scene classification: Benchmark and state of the art

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:11:45.881634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:11:45.507357Z digest=sha256:a4e1693539eecf9f997fdd0e6354331b8cd81c6c1b11941ad92027d1a255e311

Observation 92cfd410-de22-43aa-b927-4c89015c0d53 · outbound

This paper cites Bag-of-visual-words and spatial extensions for land-use classification.

MambaOutRS: A Hybrid CNN-Fourier Architecture for Remote Sensing Image Classification Bag-of-visual-words and spatial extensions for land-use classification

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:11:45.713787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:11:45.553123Z digest=sha256:35a5c59638b10a521de59e05fbc60e6a3abf91602fa027deef0628651442156e

Pith citing papers

No inbound Pith citation observations are available.