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Paper Citation Record · LEDGER

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection

As of 7 August 2026, this Paper Citation Record lists 93 of 93 outbound references and 0 inbound Pith citation observations for arXiv:2509.09572.

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

pith.paper-citation-record.v1
2509.09572 v1

Coverage vector

measured 93 of 93 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T18:55:36.151738Z

measured 93 of 93 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

93 of 93 outbound references displayed

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  • unresolved93
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  • malformed identifier0
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Outbound references

Observation f5156f77-2535-4ba7-b43a-1cbba4ca9cd3 · outbound

This paper cites Segment anything,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Segment anything,

Reference 1

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Observation a26fe90a-b8a5-4e34-a1e5-decf9b325a44 · outbound

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

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Emerging properties in self-supervised vision transformers,

Reference 2

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Observation 0dee32a7-b8c2-4df6-95e2-86fe16e57298 · outbound

This paper cites DINOv3.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection DINOv3

Reference 3

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Observation 6c2576db-f20d-4727-b542-413e09737d58 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Learning transferable visual models from natural language supervision,

Reference 4

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Observation 2f20bdd3-3a63-4cb0-baab-958942487665 · outbound

This paper cites Lora: Low-rank adaptation of large language models,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Lora: Low-rank adaptation of large language models,

Reference 5

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Observation 04101070-b4e4-4903-b0c4-698c6a7cc7b9 · outbound

This paper cites Parameter-efficient transfer learning for nlp,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Parameter-efficient transfer learning for nlp,

Reference 6

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Observation d804a15f-26a3-4925-8a8f-435dc1e3494e · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection LoRA: Low-Rank Adaptation of Large Language Models

Reference 7

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Observation dbbfab78-18fc-4ece-998f-dd4b5f8a4b2b · outbound

This paper cites iBOT: Image BERT Pre-Training with Online Tokenizer.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection iBOT: Image BERT Pre-Training with Online Tokenizer

Reference 8

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Observation 822ceed2-24ae-4e43-b45a-cf921c9ff1fc · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection SAM 2: Segment Anything in Images and Videos

Reference 9

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Observation cea45b3b-8ef7-4398-97bc-86a9ccb84638 · outbound

This paper cites Adapting segment anything model for change detection in vhr remote sensing images,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Adapting segment anything model for change detection in vhr remote sensing images,

Reference 10

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Observation 321f38e8-b0c5-400d-9a61-91873dd93098 · outbound

This paper cites Integrating sam with feature interaction for remote sensing change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Integrating sam with feature interaction for remote sensing change detection,

Reference 11

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Observation ea0c8bdb-a787-4b89-81de-ad169b664658 · outbound

This paper cites Adapting Vision Transformer for Efficient Change Detection.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Adapting Vision Transformer for Efficient Change Detection

Reference 12

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Observation d72eea6f-4a05-428c-b09d-213f78c02d4b · outbound

This paper cites Integrating deep change vector analysis and sam for class-specific change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Integrating deep change vector analysis and sam for class-specific change detection,

Reference 13

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Observation a825993d-7921-48f7-a87c-7f7152ba5033 · outbound

This paper cites A spatial-temporal attention-based method and a new dataset for remote sensing image change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection A spatial-temporal attention-based method and a new dataset for remote sensing image change detection,

Reference 14

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Observation 9f0920a5-66cd-4e4a-bf85-6b668dac50d1 · outbound

This paper cites Change dino: A unified transformer-based framework for object-level change detection and segmentation in remote sensing imagery,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Change dino: A unified transformer-based framework for object-level change detection and segmentation in remote sensing imagery,

Reference 15

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Observation 07a1f416-62b0-4ab5-aeaa-55dbb9d4a3d9 · outbound

This paper cites Remote Sensing Image Change Detection with Transformers.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Remote Sensing Image Change Detection with Transformers

Reference 16

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Observation acc1c193-2332-4283-a124-e6f77046efa6 · outbound

This paper cites A deeply supervised attention metric-based network and an open aerial image dataset for remote sensing change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection A deeply supervised attention metric-based network and an open aerial image dataset for remote sensing change detection,

Reference 17

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Observation db14658b-3f75-43f6-9a05-986b534a89b2 · outbound

This paper cites Hybrid attention-aware transformer network collaborative multiscale feature alignment for building change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Hybrid attention-aware transformer network collaborative multiscale feature alignment for building change detection,

Reference 18

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Observation 879256a5-d889-4761-8609-24b8a47385fb · outbound

This paper cites Transition is a process: Pair-to-video change detection networks for very high resolution remote sensing images,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Transition is a process: Pair-to-video change detection networks for very high resolution remote sensing images,

Reference 19

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Observation 69e6867e-e597-430c-a0e2-516c37cd64d6 · outbound

This paper cites Joint variation learning of fusion and difference features for change detection in remote sensing images,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Joint variation learning of fusion and difference features for change detection in remote sensing images,

Reference 20

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Observation c1797996-5f1c-4d0b-89ed-57cd64817c38 · outbound

This paper cites an unresolved cited work.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Unresolved cited work

Reference 21

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Observation 2f4ff979-17f0-4f44-81c5-96c37ee61bff · outbound

This paper cites Bitemporal attention sharing network for remote sensing image change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Bitemporal attention sharing network for remote sensing image change detection,

Reference 22

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Observation 0894d058-f002-4925-a03b-641bf81bf161 · outbound

This paper cites Robust change detection for remote sensing images based on temporospatial interactive attention module,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Robust change detection for remote sensing images based on temporospatial interactive attention module,

Reference 23

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Observation 1ad754aa-654e-4265-ba9d-9eb2b8640c33 · outbound

This paper cites Agformer: An anchor- guided transformer for class imbalance in remote sensing change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Agformer: An anchor- guided transformer for class imbalance in remote sensing change detection,

Reference 24

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Observation f30d0e40-03c5-423c-a23a-4bf494556db8 · outbound

This paper cites Changeclip: Remote sensing change detection with multimodal vision-language representation learn- ing,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Changeclip: Remote sensing change detection with multimodal vision-language representation learn- ing,

Reference 25

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Observation b5a6006f-995d-41a8-8b52-a609eeeaba67 · outbound

This paper cites Changemamba: Re- mote sensing change detection with spatiotemporal state space model,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Changemamba: Re- mote sensing change detection with spatiotemporal state space model,

Reference 26

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Observation 158d308f-5dc8-4e13-8684-40b95d66a7f3 · outbound

This paper cites Exchanging dual- encoder–decoder: A new strategy for change detection with semantic guidance and spatial localization,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Exchanging dual- encoder–decoder: A new strategy for change detection with semantic guidance and spatial localization,

Reference 27

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Observation 2e2ddf07-5502-4d7f-b0c5-d87b70f5772e · outbound

This paper cites Difference-aware multiscale feature aggregation network for building change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Difference-aware multiscale feature aggregation network for building change detection,

Reference 28

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Observation 289e2dc9-3057-467d-974c-2e38db01dbf0 · outbound

This paper cites Difference enhancement and dependency- aware network for remote sensing images change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Difference enhancement and dependency- aware network for remote sensing images change detection,

Reference 29

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Observation 7f25d490-54f9-4776-a298-3e46e30244b1 · outbound

This paper cites Dual- granularity feature alignment for change detection in remote sensing images,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Dual- granularity feature alignment for change detection in remote sensing images,

Reference 30

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Observation b48e138e-61d5-4f9a-875d-3ce5d6c709a9 · outbound

This paper cites Overcoming the uncertainty challenges in detecting building changes from remote sensing images,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Overcoming the uncertainty challenges in detecting building changes from remote sensing images,

Reference 31

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Observation 1ae1e295-8541-4dd9-8abf-d0c315d296f0 · outbound

This paper cites Cwmamba: Leveraging cnn-mamba fusion for enhanced change detection in remote sensing images,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Cwmamba: Leveraging cnn-mamba fusion for enhanced change detection in remote sensing images,

Reference 32

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Observation 54675b9f-5994-4e9d-8780-8f053d1fcc6b · outbound

This paper cites FTA-net: Frequency-temporal-aware network for remote sensing change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection FTA-net: Frequency-temporal-aware network for remote sensing change detection,

Reference 33

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Observation 930db0ac-007d-4782-a23e-9c38eb5d20f1 · outbound

This paper cites Depthcd: Depth prompting in 2d remote sensing imagery change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Depthcd: Depth prompting in 2d remote sensing imagery change detection,

Reference 34

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Observation bf7ddd3a-2efb-4a9e-b30d-10f1060683ea · outbound

This paper cites Sam-mamba:a two-stage change detection network combining the adapting segment anything and mamba models,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Sam-mamba:a two-stage change detection network combining the adapting segment anything and mamba models,

Reference 35

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Observation 03408397-811f-4126-b378-dd92267c9872 · outbound

This paper cites A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sensing images,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sensing images,

Reference 36

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Observation d6ed3afb-302a-4017-b0ca-462978a930c2 · outbound

This paper cites Cd-stmamba: Toward remote sensing image change detection with spatio-temporal interaction mamba model,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Cd-stmamba: Toward remote sensing image change detection with spatio-temporal interaction mamba model,

Reference 37

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Observation 8e8099ff-1a2c-4786-b19c-07c783e9ace9 · outbound

This paper cites Hcgmnet: A hierarchical change guiding map network for change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Hcgmnet: A hierarchical change guiding map network for change detection,

Reference 38

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Observation 18045c95-bfbc-42ec-9adb-b7475aa87cbd · outbound

This paper cites Change guiding network: Incorporating change prior to guide change detection in remote sensing imagery,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Change guiding network: Incorporating change prior to guide change detection in remote sensing imagery,

Reference 39

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Observation 1b3c1b30-a9d5-4311-a42f-6fdc5e129cd1 · outbound

This paper cites A CNN-transformer network with multiscale context aggregation for fine-grained cropland change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection A CNN-transformer network with multiscale context aggregation for fine-grained cropland change detection,

Reference 40

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Observation 4cb1ba6d-933a-4eb0-a8ad-ec6a173b2d23 · outbound

This paper cites Beyond cross-temporal difference: Style-aligned and fusion-difference learning for change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Beyond cross-temporal difference: Style-aligned and fusion-difference learning for change detection,

Reference 41

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Observation 7b6463dc-e341-4438-af5c-3cf4c02ab2b7 · outbound

This paper cites Feature hierarchical differentiation for remote sensing image change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Feature hierarchical differentiation for remote sensing image change detection,

Reference 42

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Observation 6474d2ae-68f2-459b-8e8c-1967d348c385 · outbound

This paper cites Efficientcd: A new strategy for change detection based with bi-temporal layers exchanged,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Efficientcd: A new strategy for change detection based with bi-temporal layers exchanged,

Reference 43

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Observation 56b82bdf-3a95-4805-8601-ce5264e67c2b · outbound

This paper cites Change detection on remote sensing images using dual-branch multilevel intertemporal network,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Change detection on remote sensing images using dual-branch multilevel intertemporal network,

Reference 44

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Observation 8f2d1542-b75d-4c5f-820f-3e7c33bcaac4 · outbound

This paper cites Aegl-net: Adaptive multiscale global–local feature fusion network for remote sensing change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Aegl-net: Adaptive multiscale global–local feature fusion network for remote sensing change detection,

Reference 45

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Observation ab1444d4-545b-45bf-82fe-05460b2eff80 · outbound

This paper cites Adapting segment anything model for change detection in vhr remote sensing images,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Adapting segment anything model for change detection in vhr remote sensing images,

Reference 46

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Observation 619142ba-65bf-49f6-99ac-e76ad0fbaa86 · outbound

This paper cites SGANet: A siamese geometry-aware network for remote sensing change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection SGANet: A siamese geometry-aware network for remote sensing change detection,

Reference 47

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Observation 95e875f5-cbff-4b33-a5e5-592f5b23edd8 · outbound

This paper cites Changer: Feature interaction is what you need for change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Changer: Feature interaction is what you need for change detection,

Reference 48

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Observation 940bef30-d8e2-4803-8fc3-8187c5965567 · outbound

This paper cites Hfifnet: Hierarchical feature interaction network with multiscale fusion for change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Hfifnet: Hierarchical feature interaction network with multiscale fusion for change detection,

Reference 49

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Observation e8b9aeed-0b18-4fb5-9479-303d35a5851b · outbound

This paper cites Deep residual learning for image recognition,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Deep residual learning for image recognition,

Reference 50

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Observation 31f426d8-21cd-4862-b879-8e51d369f850 · outbound

This paper cites A transformer-based siamese net- work for change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection A transformer-based siamese net- work for change detection,

Reference 51

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Observation ca0a2d09-a99e-4a3b-a451-005bf6648ef3 · outbound

This paper cites FCCDN: Feature Constraint Network for VHR Image Change Detection.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection FCCDN: Feature Constraint Network for VHR Image Change Detection

Reference 52

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Observation 334be6db-ee45-4af8-bb8c-a7c5c76e01f9 · outbound

This paper cites Convformer-cd: Hybrid cnn–transformer with temporal attention for detecting changes in remote sensing imagery,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Convformer-cd: Hybrid cnn–transformer with temporal attention for detecting changes in remote sensing imagery,

Reference 53

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Observation c37873c5-ff4a-4b10-abba-dcb08b11e4f8 · outbound

This paper cites Eatder: Edge-assisted adaptive transformer detector for remote sensing change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Eatder: Edge-assisted adaptive transformer detector for remote sensing change detection,

Reference 54

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Observation 948b6cc7-6347-4942-b306-7378ca9f8ef6 · outbound

This paper cites Network and dataset for multiscale remote sensing image change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Network and dataset for multiscale remote sensing image change detection,

Reference 55

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Observation 27e206cb-bc2b-4bd6-8f01-8ca31fd74f65 · outbound

This paper cites Full-scale change detection network for remote sensing images based on deep feature fusion,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Full-scale change detection network for remote sensing images based on deep feature fusion,

Reference 56

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Observation d29970cd-200d-4621-b66b-7c422294349a · outbound

This paper cites Aanet: An ambiguity-aware network for remote-sensing image change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Aanet: An ambiguity-aware network for remote-sensing image change detection,

Reference 57

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Observation dca31889-01a9-4375-a1f6-bcaec8a1a230 · outbound

This paper cites Sam-based efficient feature integration network for remote sensing change detection: A case study on macao sea reclamation,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Sam-based efficient feature integration network for remote sensing change detection: A case study on macao sea reclamation,

Reference 58

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Observation f4ac37f9-6afc-4b6d-8538-ae7274c0d469 · outbound

This paper cites Feature pyramid networks for object detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Feature pyramid networks for object detection,

Reference 59

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Observation c175e72d-e067-4e72-bdcb-a3f3c8c58942 · outbound

This paper cites Available: https://api.semanticscholar.org/CorpusID: 275032911.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Available: https://api.semanticscholar.org/CorpusID: 275032911

Reference 60

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Observation c1b1d23c-7ed9-461a-8579-53bba37966b9 · outbound

This paper cites CDMamba: Incorporating local clues into mamba for remote sensing image binary change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection CDMamba: Incorporating local clues into mamba for remote sensing image binary change detection,

Reference 61

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Observation 35bcca02-cd6c-4a14-b517-e75c851cc2dd · outbound

This paper cites Interactive and supervised dual-mode attention network for remote sensing image change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Interactive and supervised dual-mode attention network for remote sensing image change detection,

Reference 62

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Observation d06f7f8f-d2a9-43ff-bc8a-dd10e3de24f0 · outbound

This paper cites ELGC- net: Efficient local–global context aggregation for remote sensing change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection ELGC- net: Efficient local–global context aggregation for remote sensing change detection,

Reference 63

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Observation c93de997-e1f9-43cd-b4d4-bc7e460dfd4c · outbound

This paper cites Available: https://api.semanticscholar.org/CorpusID: 279733460.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Available: https://api.semanticscholar.org/CorpusID: 279733460

Reference 64

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Observation 0908939d-6329-4f62-aa47-bda3a1b277cb · outbound

This paper cites A deep supervised change detection network based on context-rich information,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection A deep supervised change detection network based on context-rich information,

Reference 65

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Observation 7065b743-2843-47da-a544-79813cb656e7 · outbound

This paper cites Cross attention is all you need: relational remote sensing change detection with transformer,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Cross attention is all you need: relational remote sensing change detection with transformer,

Reference 66

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Observation e96d5651-babf-4b75-ab71-066418d014a7 · outbound

This paper cites Remote sensing change detection with transformers trained from scratch,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Remote sensing change detection with transformers trained from scratch,

Reference 67

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Observation ba1e86b9-5680-45ee-a88e-943a36612dd9 · outbound

This paper cites Sffce-cd: Spatial and frequency feature cross enhancement for change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Sffce-cd: Spatial and frequency feature cross enhancement for change detection,

Reference 68

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Observation 2eb61353-b84d-4c62-9ac5-a5bf51f185fa · outbound

This paper cites DSFI-CD: Diffusion- guided spatial-frequency-domain information interaction for remote sensing image change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection DSFI-CD: Diffusion- guided spatial-frequency-domain information interaction for remote sensing image change detection,

Reference 69

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Observation 009e22de-553b-4257-bff0-0a24e46a9f2d · outbound

This paper cites Global- aware siamese network for change detection on remote sensing images,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Global- aware siamese network for change detection on remote sensing images,

Reference 70

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Observation 9873e5bb-6240-4adb-8a2b-95b27652fe53 · outbound

This paper cites Mfatnet: Multi-scale feature aggregation via transformer for remote sensing image change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Mfatnet: Multi-scale feature aggregation via transformer for remote sensing image change detection,

Reference 71

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Observation 813dc331-18a2-4f21-970f-8a1c5be5cacd · outbound

This paper cites MLDFNet: A multilabel dual- flow network for change detection in bitemporal remote sensing images,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection MLDFNet: A multilabel dual- flow network for change detection in bitemporal remote sensing images,

Reference 72

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Observation f21115db-e98b-46f1-9efa-17b97fda0fc3 · outbound

This paper cites B2cnet: A progressive change boundary-to-center refinement network for multitemporal remote sensing images change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection B2cnet: A progressive change boundary-to-center refinement network for multitemporal remote sensing images change detection,

Reference 73

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source=pdf_text observed=2026-08-04T18:55:36.077448Z digest=sha256:71096730012cb8a034ede995ad1971688029abbdf6994981ca8a32d79d41bc49

Observation 7461d09c-44e7-41cb-ace7-516a549822c5 · outbound

This paper cites Dual fine-grained network with frequency transformer for change detection on remote sensing images,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Dual fine-grained network with frequency transformer for change detection on remote sensing images,

Reference 74

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source=pdf_text observed=2026-08-04T18:55:36.045164Z digest=sha256:3410efff7c55a145904e8952d95f76d72fde0d42300e7a8105f0fbd0e88945f8

Observation 98d70e67-170b-4586-85a3-e490afb3ef7e · outbound

This paper cites Stransunet: A siamese transunet- based remote sensing image change detection network,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Stransunet: A siamese transunet- based remote sensing image change detection network,

Reference 75

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source=pdf_text observed=2026-08-04T18:55:36.088550Z digest=sha256:eb4cfa97eae57afdd6eb1bb4bf33af26d847ad80c0b40f4e65f887fa58fc516a

Observation 5a5dcbbd-82d5-461e-a38b-6f0a15d98783 · outbound

This paper cites HASNet: A foreground association-driven siamese network with hard sample opti- mization for remote sensing image change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection HASNet: A foreground association-driven siamese network with hard sample opti- mization for remote sensing image change detection,

Reference 76

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source=pdf_text observed=2026-08-04T18:55:36.055770Z digest=sha256:5893367c93d7ceeaa14178cb724cf6cbf905990172a6fcf8895acb319551f2e8

Observation 1722c525-924e-4ecd-acaa-3fe144d79873 · outbound

This paper cites Fully convolutional networks for multisource building extraction from an open aerial and satellite imagery data set,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Fully convolutional networks for multisource building extraction from an open aerial and satellite imagery data set,

Reference 77

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source=pdf_text observed=2026-08-04T18:55:36.105068Z digest=sha256:9149d448d997749fd523c62a57e5f2b1509bf28f86f8953762ddea26527b5fec

Observation bf039403-6ebd-4a6c-bd73-ab41525bd5df · outbound

This paper cites An attention-based multiscale transformer network for remote sensing image change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection An attention-based multiscale transformer network for remote sensing image change detection,

Reference 78

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source=pdf_text observed=2026-08-04T18:55:36.066348Z digest=sha256:4cb4301e77dbc90726a6176577bfebc116f13288daabbd14ba179a371538d8bf

Observation a4a8dcfb-5d5b-45f8-870c-30a0f527b3d7 · outbound

This paper cites S2looking: A satellite side-looking dataset for building change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection S2looking: A satellite side-looking dataset for building change detection,

Reference 79

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source=pdf_text observed=2026-08-04T18:55:36.122630Z digest=sha256:4441b2563c70b8d10c674b7f5bef86c80718ccd667ee8e4afd39e311d4481634

Observation 763e31e0-6275-4ddf-b822-23f955aae931 · outbound

This paper cites Rs-mamba for large remote sensing image dense prediction,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Rs-mamba for large remote sensing image dense prediction,

Reference 80

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source=pdf_text observed=2026-08-04T18:55:36.134912Z digest=sha256:f75dce4b05b5bc6bf852054e5475c1c4556ae68aa83126c83643655deca51be0

Observation 1a02199d-1700-4b9c-be79-8c014269bd3e · outbound

This paper cites Remote sensing image change detection transformer network based on dual-feature mixed attention,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Remote sensing image change detection transformer network based on dual-feature mixed attention,

Reference 81

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source=pdf_text observed=2026-08-04T18:55:36.083027Z digest=sha256:9ef3926d5148fb1d89ed594256806a85c42799cf717f0652b5b3918306a20960

Observation 14cadf31-ded6-44ef-af8f-fb660f54e2e4 · outbound

This paper cites Transunetcd: A hybrid transformer network for change detection in optical remote-sensing images,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Transunetcd: A hybrid transformer network for change detection in optical remote-sensing images,

Reference 82

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source=pdf_text observed=2026-08-04T18:55:36.146461Z digest=sha256:2736b019b7efdb92e24d505bebb6405d8538a520d8c2d015eff7e3d7fc9b581c

Observation 5d652b55-d88f-42e1-8010-fe207ee52250 · outbound

This paper cites Lccdmamba: Visual state space model for land cover change detection of vhr remote sensing images,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Lccdmamba: Visual state space model for land cover change detection of vhr remote sensing images,

Reference 83

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Observation 67edb819-f0ff-4b9d-95d2-8cfd73058ba1 · outbound

This paper cites Available: https://api.semanticscholar.org/CorpusID: 275776209.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Available: https://api.semanticscholar.org/CorpusID: 275776209

Reference 84

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Observation 96df39a2-cf4a-424d-832c-7c035678cbe8 · outbound

This paper cites Change detection in remote sensing images using conditional adversarial networks,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Change detection in remote sensing images using conditional adversarial networks,

Reference 86

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Observation fd43ff0c-6962-4c94-a6cd-d8f83297cf20 · outbound

This paper cites Available: https://api.semanticscholar.org/CorpusID: 236134438.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Available: https://api.semanticscholar.org/CorpusID: 236134438

Reference 89

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Observation 8dfb89d6-75f9-4e96-8aef-f265560255f0 · outbound

This paper cites Swinsunet: Pure transformer network for remote sensing image change detection,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Swinsunet: Pure transformer network for remote sensing image change detection,

Reference 91

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Observation 5b06bb8d-9ee4-416b-853f-fa0e5e8c9e27 · outbound

This paper cites Dc-mamba: A novel network for enhanced remote sensing change detection in difficult cases,.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Dc-mamba: A novel network for enhanced remote sensing change detection in difficult cases,

Reference 93

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Observation 3c6bc8e6-510c-4cc5-b20d-600577eca7d7 · outbound

This paper cites Available: https://api.semanticscholar.org/CorpusID: 57660599.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Available: https://api.semanticscholar.org/CorpusID: 57660599

Reference 2018

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Observation e6084d0b-5a41-4847-916d-694404db53b8 · outbound

This paper cites Available: https://api.semanticscholar.org/CorpusID: 225504855.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Available: https://api.semanticscholar.org/CorpusID: 225504855

Reference 2020

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Observation a51e173b-daf3-4d92-9494-a7d6185e6055 · outbound

This paper cites Available: https://api.semanticscholar.org/CorpusID: 231591445.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Available: https://api.semanticscholar.org/CorpusID: 231591445

Reference 2021

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Observation 1fe30506-d644-45d7-b728-13bb8b46ec26 · outbound

This paper cites Available: https://api.semanticscholar.org/CorpusID: 259931492.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Available: https://api.semanticscholar.org/CorpusID: 259931492

Reference 2023

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Observation 52cfa0b6-99cd-4a50-946e-a6c30a5beb28 · outbound

This paper cites Available: https://api.semanticscholar.org/CorpusID: 275486271.

PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection Available: https://api.semanticscholar.org/CorpusID: 275486271

Reference 2025

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Pith citing papers

No inbound Pith citation observations are available.