Paper Citation Record · LEDGER

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types

As of 11 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 1 inbound Pith citation observation for arXiv:2502.01162.

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

pith.paper-citation-record.v1
2502.01162 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T16:26:09.025943Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T16:26:08.943744Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T16:26:09.065711Z

Reference resolution

24 of 24 outbound references displayed

verified exact1
verified fuzzy20
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f87f1e9e-17c9-437f-a99a-9e991a2f68ed · outbound

This paper cites Widely employed to monitor various activities, SAR plays a crucial role in tracking urban development [2], assessing biomass changes [3], and detect- ing ships [4], for example.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types Widely employed to monitor various activities, SAR plays a crucial role in tracking urban development [2], assessing biomass changes [3], and detect- ing ships [4], for example

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.327944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation fe80978b-c66a-4881-86e8-66b677620f22 · outbound

This paper cites General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-09T16:26:09.071883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6f691e63-737f-41bd-82da-a68d8326b9a7 · outbound

This paper cites Then, the model is evaluated with qualitative and quantitative tests.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types Then, the model is evaluated with qualitative and quantitative tests

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.304280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d7e85ff5-f1f6-412c-923d-794970c2bf90 · outbound

This paper cites It underscores great adaptability across sensor types.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types It underscores great adaptability across sensor types

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.290555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6277d84c-feda-4733-8cde-660e9d0eb916 · outbound

This paper cites Self-supervised learning based anomaly de- tection in synthetic aperture radar imaging,.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types Self-supervised learning based anomaly de- tection in synthetic aperture radar imaging,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.231877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0f604394-fe43-43a0-ba97-39d2c1736ad5 · outbound

This paper cites A tutorial on synthetic aperture radar,.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types A tutorial on synthetic aperture radar,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.278372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7e429e68-7cc8-4bcb-bd71-ed1a041b80ed · outbound

This paper cites New robust statistics for change detection in time se- ries of multivariate sar images,.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types New robust statistics for change detection in time se- ries of multivariate sar images,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.267079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4710f86a-fda2-4408-95c6-3ce22f1eb798 · outbound

This paper cites Application of l-band sar for mapping tundra shrub biomass, leaf area index, and rainfall interception,.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types Application of l-band sar for mapping tundra shrub biomass, leaf area index, and rainfall interception,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.255260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e4e72ffa-3454-4ca1-96b0-b5cf93a2503b · outbound

This paper cites Ship detection in sar im- ages based on an improved faster r-cnn,.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types Ship detection in sar im- ages based on an improved faster r-cnn,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.243607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7d0c0bf8-ac33-4d50-8fb9-bfedf0b45c5d · outbound

This paper cites A Cookbook of Self-Supervised Learning.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types A Cookbook of Self-Supervised Learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T16:26:08.992879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff2deaef-72f0-4c7f-a0f0-43943b69bae6 · outbound

This paper cites Beets or cotton? blind extraction of fine agricultural classes using a convolutional autoen- coder applied to temporal sar signatures,.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types Beets or cotton? blind extraction of fine agricultural classes using a convolutional autoen- coder applied to temporal sar signatures,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.220883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8c9da4b9-cd81-4370-863d-e272b102de6f · outbound

This paper cites Target recognition in sar images by deep learning with training data augmentation,.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types Target recognition in sar images by deep learning with training data augmentation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.208997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2ce52dd8-378b-4637-baa2-1dd7d2d20e34 · outbound

This paper cites Self- supervised feature representation for sar image target classification using contrastive learning,.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types Self- supervised feature representation for sar image target classification using contrastive learning,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.196505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d906049c-703d-4bee-a7e4-f2bb6e9b0958 · outbound

This paper cites An image is worth 16x16 words: Trans- formers for image recognition at scale,.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types An image is worth 16x16 words: Trans- formers for image recognition at scale,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.184420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 161e31c0-b82a-4704-8f7e-816aad29b3e0 · outbound

This paper cites Each image is encoded by a ViT (fθstudent or fθteacher) in a feature z ∈ Rde, then projected with a multilayer perceptron head ( Wθstudent or Wθteacher) in a representation h ∈ Rdh.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types Each image is encoded by a ViT (fθstudent or fθteacher) in a feature z ∈ Rde, then projected with a multilayer perceptron head ( Wθstudent or Wθteacher) in a representation h ∈ Rdh

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.315663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e6cdce93-c442-466c-a3a9-c1345d6cff6c · outbound

This paper cites SETHI: Review of 10 years of development and experimentation of the remote sensing platform,.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types SETHI: Review of 10 years of development and experimentation of the remote sensing platform,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.172623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2694bd3b-dde3-4186-9066-5122b0f4db7d · outbound

This paper cites Gen- eralizing from a few examples: A survey on few-shot learning,.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types Gen- eralizing from a few examples: A survey on few-shot learning,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.160830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation dc9e01b1-9919-4476-9502-e87376943cfe · outbound

This paper cites Signature verification using a.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types Signature verification using a

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.149561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 09479936-e6ff-4e2a-9281-cd16dac09735 · outbound

This paper cites Emerging properties in self-supervised vision transformers,.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types Emerging properties in self-supervised vision transformers,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T16:26:09.007337Z

Source-reported events for the cited work

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Observation 64bb7cff-d54e-429f-8527-30bed9fc2253 · outbound

This paper cites Masked siamese networks for label-efficient learning,.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types Masked siamese networks for label-efficient learning,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.131164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a017bcdd-546a-4573-ba90-f57c429c8522 · outbound

This paper cites A simple framework for contrastive learning of visual rep- resentations,.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types A simple framework for contrastive learning of visual rep- resentations,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.119362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c0419b07-a446-41f4-9755-ac46e23833eb · outbound

This paper cites Subband ex- traction strategies in ship detection with the subaperture cross-correlation magnitude,.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types Subband ex- traction strategies in ship detection with the subaperture cross-correlation magnitude,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.106929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 06969454-2e9f-4aad-8b9e-26e7d877cf80 · outbound

This paper cites Some fundamental properties of speckle,.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types Some fundamental properties of speckle,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-09T16:26:09.022187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2233377a-0209-43af-abe0-717f2524a1c6 · outbound

This paper cites As if by magic: self-supervised training of deep despeckling networks with MERLIN,.

General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types As if by magic: self-supervised training of deep despeckling networks with MERLIN,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:26:09.084190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

Observation fe80978b-c66a-4881-86e8-66b677620f22 · inbound