Paper Citation Record · LEDGER

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype

As of 17 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2504.19074.

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

pith.paper-citation-record.v1
2504.19074 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T06:06:08.885625Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

17 of 17 outbound references displayed

verified exact0
verified fuzzy13
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 887334b4-03ad-4b37-a7ff-ab17ebcdf174 · outbound

This paper cites Spectral–spatial classification of hyper- spectral imagery with 3d convolutional neural network,.

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype Spectral–spatial classification of hyper- spectral imagery with 3d convolutional neural network,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:09.132974Z

Source-reported events for the cited work

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Observation feab0dd8-2f92-4c75-9613-a2f8a6a19e88 · outbound

This paper cites Spectral–spatial residual network for hyperspectral image classification: A 3-d deep learning framework,.

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype Spectral–spatial residual network for hyperspectral image classification: A 3-d deep learning framework,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T06:06:08.820241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62bd0f64-4cd7-4076-8d5a-12c3e96b8431 · outbound

This paper cites Domain-adversarial training of neural networks,.

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype Domain-adversarial training of neural networks,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T06:06:08.824666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92fe274e-b63d-4746-886b-73a75e37e28c · outbound

This paper cites Transfer feature learning with joint distribution adaptation,.

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype Transfer feature learning with joint distribution adaptation,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:09.100973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b4ec1c38-97e8-4529-905b-4abb6d4552af · outbound

This paper cites Deep few-shot learning for hyperspectral image classification,.

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype Deep few-shot learning for hyperspectral image classification,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T06:06:08.833706Z

Source-reported events for the cited work

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Observation d3e184f9-e14e-45c4-b6ce-6f8a19ad0d51 · outbound

This paper cites Few-shot learning with class-covariance metric for hyperspectral image classifica- tion,.

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype Few-shot learning with class-covariance metric for hyperspectral image classifica- tion,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:09.077717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 68143787-a265-44bc-a71b-740923ed745d · outbound

This paper cites Sdst: Self-supervised double-structure transformer for hyperspectral images clustering,.

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype Sdst: Self-supervised double-structure transformer for hyperspectral images clustering,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:09.063724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f83b0112-2799-4a31-aac3-2d1c17187643 · outbound

This paper cites Multiscale diff-changed feature fusion network for hyperspectral image change detection,.

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype Multiscale diff-changed feature fusion network for hyperspectral image change detection,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:09.050048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 845dde6b-d606-4831-bc4d-fbf2fa05e99b · outbound

This paper cites Few- shot learning with prototype rectification for cross-domain hyperspectral image classification,.

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype Few- shot learning with prototype rectification for cross-domain hyperspectral image classification,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:09.036452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6ac8690e-88ca-4b38-9833-8314517264a3 · outbound

This paper cites Deep updated subspace networks for few-shot remote sensing scene classification,.

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype Deep updated subspace networks for few-shot remote sensing scene classification,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:09.022404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6d5e3353-e7d4-43c6-abd8-45c69e5ffecc · outbound

This paper cites Refined prototypical contrastive learning for few-shot hyperspectral image classification,.

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype Refined prototypical contrastive learning for few-shot hyperspectral image classification,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:09.007330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c46da1bf-28d1-4a17-8d37-7a8271d05e8f · outbound

This paper cites Cross-domain few-shot hyper- spectral image classification with class-wise attention,.

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype Cross-domain few-shot hyper- spectral image classification with class-wise attention,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:08.991598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fe12f69c-07e6-4705-83aa-8c4cc74f3d9d · outbound

This paper cites Mish: A Self Regularized Non-Monotonic Activation Function.

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype Mish: A Self Regularized Non-Monotonic Activation Function

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T06:06:08.868618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e923b18-35f1-4349-96de-4c339dbf732b · outbound

This paper cites Deep cross- domain few-shot learning for hyperspectral image classification,.

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype Deep cross- domain few-shot learning for hyperspectral image classification,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:08.977112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cd6ea50d-1826-487f-aae5-35776a683d81 · outbound

This paper cites Graph information aggregation cross-domain few-shot learning for hyperspec- tral image classification,.

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype Graph information aggregation cross-domain few-shot learning for hyperspec- tral image classification,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:08.963870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3c92cf6d-cc50-4332-a5c6-322fac8eaeb1 · outbound

This paper cites Distribution-aware and class-adaptive aggregation for few-shot hyperspectral image classifica- tion,.

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype Distribution-aware and class-adaptive aggregation for few-shot hyperspectral image classifica- tion,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:08.949605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 86a1df35-fc1a-4d94-9da0-9b085cd7e247 · outbound

This paper cites Cross-domain few-shot learning based on feature disentanglement for hyperspectral image classification,.

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype Cross-domain few-shot learning based on feature disentanglement for hyperspectral image classification,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:08.935475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

No inbound Pith citation observations are available.